The use of clustering techniques enhances the user experience and thus the success of collaborative tagging services. We show that clustering techniques can improve the user experience of current tagging services. We first describe current limitations of tagging services, second, we give an overview of existing approaches. We then describe the algorithms we used for tag clustering and give experimental results and a variety of conclusions.

@inproceedings{begelman2006automated, author = {Begelman, Grigory and Keller, Philipp and Smadja, Frank}, title = {Automated Tag Clustering: Improving search and exploration in the tag space}, booktitle = {Proceedings of the Collaborative Web Tagging Workshop at the WWW 2006}, address = {Edinburgh, Scotland}, year = {2006}, url = {http://.pui.ch/phred/automated_tag_clustering/}, keywords = {closely_related, diploma_thesis, ol_web2.0, methods_synonyms, methods_concepthierarchy}, abstract = {The use of clustering techniques enhances the user experience and thus the success of collaborative tagging services. We show that clustering techniques can improve the user experience of current tagging services. We first describe current limitations of tagging services, second, we give an overview of existing approaches. We then describe the algorithms we used for tag clustering and give experimental results and a variety of conclusions.} }

%0 = inproceedings %A = Begelman, Grigory and Keller, Philipp and Smadja, Frank %B = Proceedings of the Collaborative Web Tagging Workshop at the WWW 2006 %C = Edinburgh, Scotland %D = 2006 %T = Automated Tag Clustering: Improving search and exploration in the tag space %U = http://.pui.ch/phred/automated_tag_clustering/

A key argument for modeling knowledge in ontologies is the easy re-use and re-engineering of the knowledge. However, current ontology engineering tools provide only basic functionalities for analyzing ontologies. Since ontologies can be considered as graphs, graph analysis techniques are a suitable answer for this need. Graph analysis has been performed by sociologists for over 60 years, and resulted in the vivid research area of Social Network Analysis (SNA). While social network structures currently receive high attention in the Semantic Web community, there are only very few SNA applications, and virtually none for analyzing the structure of ontologies. We illustrate the benefits of applying SNA to ontologies and the Semantic Web, and discuss which research topics arise on the edge between the two areas. In particular, we discuss how different notions of centrality describe the core content and structure of an ontology. From the rather simple notion of degree centrality over betweenness centrality to the more complex eigenvector centrality, we illustrate the insights these measures provide on two ontologies, which are different in purpose, scope, and size.

@inproceedings{hoser2006semantic, author = {Hoser, Bettina and Hotho, Andreas and J�schke, Robert and Schmitz, Christoph and Stumme, Gerd}, title = {Semantic Network Analysis of Ontologies}, booktitle = {European Semantic Web Conference, Budva, Montenegro}, year = {2006}, url = {http://www.eswc2006.org/}, keywords = {closely_related, diploma_thesis}, abstract = {A key argument for modeling knowledge in ontologies is the easy re-use and re-engineering of the knowledge. However, current ontology engineering tools provide only basic functionalities for analyzing ontologies. Since ontologies can be considered as graphs, graph analysis techniques are a suitable answer for this need. Graph analysis has been performed by sociologists for over 60 years, and resulted in the vivid research area of Social Network Analysis (SNA). While social network structures currently receive high attention in the Semantic Web community, there are only very few SNA applications, and virtually none for analyzing the structure of ontologies. We illustrate the benefits of applying SNA to ontologies and the Semantic Web, and discuss which research topics arise on the edge between the two areas. In particular, we discuss how different notions of centrality describe the core content and structure of an ontology. From the rather simple notion of degree centrality over betweenness centrality to the more complex eigenvector centrality, we illustrate the insights these measures provide on two ontologies, which are different in purpose, scope, and size.} }

%0 = inproceedings %A = Hoser, Bettina and Hotho, Andreas and J�schke, Robert and Schmitz, Christoph and Stumme, Gerd %B = European Semantic Web Conference, Budva, Montenegro %D = 2006 %T = Semantic Network Analysis of Ontologies %U = http://www.eswc2006.org/

Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. At the moment, however, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies, called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to find communities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset.

@inproceedings{hotho06-information, author = {Hotho, Andreas and J�schke, Robert and Schmitz, Christoph and Stumme, Gerd}, title = {Information Retrieval in Folksonomies: Search and Ranking}, editor = {Sure, York and Domingue, John}, booktitle = {The Semantic Web: Research and Applications}, series = {LNAI}, publisher = {Springer}, address = {Heidelberg}, year = {2006}, volume = {4011}, pages = {411-426}, url = {http://.kde.cs.uni-kassel.de/hotho}, keywords = {bibsonomy, closely_related, diploma_thesis, folkrank, ranking, search}, abstract = {Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. At the moment, however, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies, called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to find communities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset.} }

%0 = inproceedings %A = Hotho, Andreas and J�schke, Robert and Schmitz, Christoph and Stumme, Gerd %B = The Semantic Web: Research and Applications %C = Heidelberg %D = 2006 %I = Springer %T = Information Retrieval in Folksonomies: Search and Ranking %U = http://.kde.cs.uni-kassel.de/hotho

GiveALink.org is a social bookmarking site where users may donate and view their personal bookmark files online se- curely. The bookmarks are analyzed to build a new gener- ation of intelligent information retrieval techniques to recom- mend, search, and personalize the Web. GiveALink does not use tags, content, or links in the submitted Web pages. Instead we present a semantic similarity measure for URLs that takes advantage both of the hierarchical structure in the bookmark files of individual users, and of collaborative filtering across users. In addition, we build a recommendation and search engine from ranking algorithms based on popularity and nov- elty measures extracted from the similarity-induced network. Search results can be personalized using the bookmarks sub- mitted by a user. We evaluate a subset of the proposed ranking measures by conducting a study with human subjects

@inproceedings{markines2006bookmark, author = {Markines, Ben and Stoilova, Lubomira and Menczer, Filippo}, title = {Bookmark Hierarchies and Collaborative Recommendation}, booktitle = {AAAI}, publisher = {AAAI Press}, year = {2006}, url = {http://www.aaai.org/Library/AAAI/aaai06contents.php}, keywords = {studienarbeit, closely_related}, abstract = {GiveALink.org is a social bookmarking site where users may donate and view their personal bookmark files online se- curely. The bookmarks are analyzed to build a new gener- ation of intelligent information retrieval techniques to recom- mend, search, and personalize the Web. GiveALink does not use tags, content, or links in the submitted Web pages. Instead we present a semantic similarity measure for URLs that takes advantage both of the hierarchical structure in the bookmark files of individual users, and of collaborative filtering across users. In addition, we build a recommendation and search engine from ranking algorithms based on popularity and nov- elty measures extracted from the similarity-induced network. Search results can be personalized using the bookmarks sub- mitted by a user. We evaluate a subset of the proposed ranking measures by conducting a study with human subjects} }

%0 = inproceedings %A = Markines, Ben and Stoilova, Lubomira and Menczer, Filippo %B = AAAI %D = 2006 %I = AAAI Press %T = Bookmark Hierarchies and Collaborative Recommendation %U = http://www.aaai.org/Library/AAAI/aaai06contents.php

This paper describes AutoTag, a tool which suggests tags for weblog posts using collaborative filtering methods. An evaluation of AutoTag on a large collection of posts shows good accuracy; coupled with the blogger's final quality control, AutoTag assists both in simplifying the tagging process and in improving its quality.

@inproceedings{mishne2006autotag, author = {Mishne, Gilad}, title = {AutoTag: a collaborative approach to automated tag assignment for weblog posts}, booktitle = {WWW '06: Proceedings of the 15th international conference on World Wide Web}, publisher = {ACM Press}, address = {New York, NY, USA}, year = {2006}, pages = {953--954}, note = {paper presented at the poster track}, url = {http://2006.org/programme/item.php?id=p11}, keywords = {closely_related, diploma_thesis}, abstract = {This paper describes AutoTag, a tool which suggests tags for weblog posts using collaborative filtering methods. An evaluation of AutoTag on a large collection of posts shows good accuracy; coupled with the blogger's final quality control, AutoTag assists both in simplifying the tagging process and in improving its quality.} }

%0 = inproceedings %A = Mishne, Gilad %B = WWW '06: Proceedings of the 15th international conference on World Wide Web %C = New York, NY, USA %D = 2006 %I = ACM Press %T = AutoTag: a collaborative approach to automated tag assignment for weblog posts %U = http://2006.org/programme/item.php?id=p11

Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. These systems provide currently relatively few structure. We discuss in this paper, how association rule mining can be adopted to analyze and structure folksonomies, and how the results can be used for ontology learning and supporting emergent semantics. We demonstrate our approach on a large scale dataset stemming from an online system.

@inproceedings{schmitz2006mining, author = {Schmitz, Christoph and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd}, title = {Mining Association Rules in Folksonomies}, editor = {Batagelj, V. and Bock, H.-H. and Ferligoj, A. and �iberna, A.}, booktitle = {Data Science and Classification. Proceedings of the 10th IFCS Conf.}, series = {Studies in Classification, Data Analysis, and Knowledge Organization}, publisher = {Springer}, address = {Heidelberg}, year = {2006}, pages = {261--270}, keywords = {analysis, closely_related, diploma_thesis, folksonomy, nepomuk, network, semantic, ol_web2.0, methods_concepts, methods_concepthierarchy}, abstract = {Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. These systems provide currently relatively few structure. We discuss in this paper, how association rule mining can be adopted to analyze and structure folksonomies, and how the results can be used for ontology learning and supporting emergent semantics. We demonstrate our approach on a large scale dataset stemming from an online system.} }

%0 = inproceedings %A = Schmitz, Christoph and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd %B = Data Science and Classification. Proceedings of the 10th IFCS Conf. %C = Heidelberg %D = 2006 %I = Springer %T = Mining Association Rules in Folksonomies

This paper delivers a case study on the properties of meta- data provided by a folksonomy. We provide the background about folk- sonomies and discuss to which extend the process of creating meta-data in a folksonomy is related to the idea of emergent semantics as defined by the IFIP 2.6 Working Group on Data Semantics. We conduct exper- iments to analyse the meta-data provided by the del.icio.us folksonomy and to develop a method for selecting subsets of meta-data that adhere to the principle of interest-based locality, which was originally observed in peer-to-peer environments. In addition, we compare data provided by del.icio.us to data provided by the DMOZ taxonomy.

@inproceedings{michlmayr2005case, author = {Michlmayr, Elke}, title = {A Case Study on Emergent Semantics in Communities}, booktitle = {Proceedings of the Workshop on Social Network Analysis, International Semantic Web Conference (ISWC)}, year = {2005}, url = {http://wit.tuwien.ac.at/people/michlmayr/index.html}, keywords = {closely_related, diploma_thesis, ol_web2.0, emergentsemantics_evidence}, abstract = {This paper delivers a case study on the properties of meta- data provided by a folksonomy. We provide the background about folk- sonomies and discuss to which extend the process of creating meta-data in a folksonomy is related to the idea of emergent semantics as defined by the IFIP 2.6 Working Group on Data Semantics. We conduct exper- iments to analyse the meta-data provided by the del.icio.us folksonomy and to develop a method for selecting subsets of meta-data that adhere to the principle of interest-based locality, which was originally observed in peer-to-peer environments. In addition, we compare data provided by del.icio.us to data provided by the DMOZ taxonomy.} }

%0 = inproceedings %A = Michlmayr, Elke %B = Proceedings of the Workshop on Social Network Analysis, International Semantic Web Conference (ISWC) %D = 2005 %T = A Case Study on Emergent Semantics in Communities %U = http://wit.tuwien.ac.at/people/michlmayr/index.html

In this paper we describe a new distributed collaborative bookmark system, called COWING (for COllaborative Web IndexING system). The COWING system is composed of a set of assistant agents, called WINGS, and a central agent that manages the user's organization. Each user is assisted by a Wing agent that performs two tasks: learning the user's strategy in classifying her/his own bookmarks and interacting with other WING agents in order to fetch new bookmarks that match the local user information need.

@inproceedings{kanawati2002multiagent, author = {Kanawati, Rushed and Malek, Maria}, title = {A multi-agent system for collaborative bookmarking}, booktitle = {AAMAS '02: Proceedings of the first international joint conference on Autonomous agents and multiagent systems}, publisher = {ACM Press}, address = {New York, NY, USA}, year = {2002}, pages = {1137--1138}, url = {portal.acm.org/citation.cfm?id=545084&coll=Portal&dl=GUIDE&CFID=51719601&CFTOKEN=55776114#}, keywords = {bookmarks, cbr, classifier, closely_related, collaborative_interface_agents, hybrid_neural-CBR_classification, studienarbeit}, abstract = {In this paper we describe a new distributed collaborative bookmark system, called COWING (for COllaborative Web IndexING system). The COWING system is composed of a set of assistant agents, called WINGS, and a central agent that manages the user's organization. Each user is assisted by a Wing agent that performs two tasks: learning the user's strategy in classifying her/his own bookmarks and interacting with other WING agents in order to fetch new bookmarks that match the local user information need.} }

%0 = inproceedings %A = Kanawati, Rushed and Malek, Maria %B = AAMAS '02: Proceedings of the first international joint conference on Autonomous agents and multiagent systems %C = New York, NY, USA %D = 2002 %I = ACM Press %T = A multi-agent system for collaborative bookmarking %U = portal.acm.org/citation.cfm?id=545084&coll=Portal&dl=GUIDE&CFID=51719601&CFTOKEN=55776114#

Taxonomic reasoning can be a useful organization paradigm to address issues dealing with the management of WWW bookmarks. Management of WWW bookmarks comprise one of the most frequent activities of WWW users. In this paper, "Babylon Bookmarks" are presented allowing users to apply taxonomic reasoning on WWW bookmarks. "Babylon Bookmarks" is based on the "Babylon System," an infrastructure to support general taxonomic reasoning tasks. The "Babylon System" allows the development of arbitrary taxonomic services based on Open Hypermedia Specifications.

@inproceedings{karousos2002babylon, author = {Karousos, Nikos and Panaretou, Ioannis and Pandis, Ippokratis and Tzagarakis, Manolis}, title = {Babylon Bookmarks: A Taxonomic Approach to the Management of WWW Bookmarks.}, booktitle = {Metainformatics}, year = {2002}, pages = {42-48}, note = {bibsource: DBLP, http://dblp.uni-trier.de}, url = {link.springer.de/link/service/series/0558/bibs/2641/26410042.htm}, keywords = {closely_related, studienarbeit}, abstract = {Taxonomic reasoning can be a useful organization paradigm to address issues dealing with the management of WWW bookmarks. Management of WWW bookmarks comprise one of the most frequent activities of WWW users. In this paper, "Babylon Bookmarks" are presented allowing users to apply taxonomic reasoning on WWW bookmarks. "Babylon Bookmarks" is based on the "Babylon System," an infrastructure to support general taxonomic reasoning tasks. The "Babylon System" allows the development of arbitrary taxonomic services based on Open Hypermedia Specifications.} }

%0 = inproceedings %A = Karousos, Nikos and Panaretou, Ioannis and Pandis, Ippokratis and Tzagarakis, Manolis %B = Metainformatics %D = 2002 %T = Babylon Bookmarks: A Taxonomic Approach to the Management of WWW Bookmarks. %U = link.springer.de/link/service/series/0558/bibs/2641/26410042.htm

@book{maedche2002ontology, author = {Maedche, Alexander}, title = {Ontology Learning for the Semantic Web}, publisher = {Kluwer Academic Publishing}, address = {Boston}, year = {2002}, keywords = {closely_related, diploma_thesis} }

%0 = book %A = Maedche, Alexander %C = Boston %D = 2002 %I = Kluwer Academic Publishing %T = Ontology Learning for the Semantic Web

Most people store 'bookmarks' to web pages. These allow the user to return to a web page later on, without having to remem- ber the exact URL address. People attempt to organise their bookmark databases by filing bookmarks under categories, themselves arranged in a hierarchical fashion. As the maintenance of such large repositories is diffcult and time-consuming, a tool that automatically categorises book- marks is required. This paper investigates how rough set theory can help extract information out of this domain, for use in an experimental auto- matic bookmark classification system. In particular, work on rough set dependency degrees is applied to reduce the otherwise high dimensional- ity of the feature patterns used to characterize bookmarks. A compari- son is made between this approach to data reduction and a conventional entropy-based approach.

@inproceedings{jensen2001rough, author = {Jensen, Richard and Shen, Qiang}, title = {A Rough Set-Aided System for Sorting WWW Bookmarks}, booktitle = {WI '01: Proceedings of the First Asia-Pacific Conference on Web Intelligence: Research and Development}, publisher = {Springer-Verlag}, address = {London, UK}, year = {2001}, pages = {95--105}, url = {jensen01.ps}, keywords = {studienarbeit, closely_related}, abstract = {Most people store 'bookmarks' to web pages. These allow the user to return to a web page later on, without having to remem- ber the exact URL address. People attempt to organise their bookmark databases by filing bookmarks under categories, themselves arranged in a hierarchical fashion. As the maintenance of such large repositories is diffcult and time-consuming, a tool that automatically categorises book- marks is required. This paper investigates how rough set theory can help extract information out of this domain, for use in an experimental auto- matic bookmark classification system. In particular, work on rough set dependency degrees is applied to reduce the otherwise high dimensional- ity of the feature patterns used to characterize bookmarks. A compari- son is made between this approach to data reduction and a conventional entropy-based approach.} }

%0 = inproceedings %A = Jensen, Richard and Shen, Qiang %B = WI '01: Proceedings of the First Asia-Pacific Conference on Web Intelligence: Research and Development %C = London, UK %D = 2001 %I = Springer-Verlag %T = A Rough Set-Aided System for Sorting WWW Bookmarks %U = jensen01.ps

A bookmark means the URL information stored for memorizing a user’s own footprints and revisiting that website. This paper regards this bookmark as one of the most meaningful information representing user preferences. An original bookmark indicating only address information is categorized for merging semantic meanings by using public web directory services. These categorized bookmarks are expressed in a hierarchical tree structure. However, most current web directory services cannot afford to normalize and manage the topic hierarchy. There are several kinds of structural incompleteness such as multiple references and heterogeneous tree structures. In order to extract user prefer-ences, this paper proposes a method for driving these problems and the influ-ence propagation methods based on Bayesian networks. Therefore, the preference maps representing users’ interests are also established as tree structures. With respect to the user clustering, an approximate tree matching method is used for mapping (overlapping) users’ preference maps. It is possible to make queries and process them efficiently according to categories. Finally, this paper is applied to implement collaborative web browsing that can guide and explore the web efficiently and adaptively.

@inproceedings{jung2001collaborative, author = {Jung, Jason J. and Yoon, Jeong-Seob and Jo, GeunSik}, title = {Collaborative Information Filtering by Using Categorized Bookmarks on the Web}, booktitle = {INAP}, year = {2001}, pages = {343-357}, url = {jung01.ps}, keywords = {studienarbeit, closely_related}, abstract = {A bookmark means the URL information stored for memorizing a user’s own footprints and revisiting that website. This paper regards this bookmark as one of the most meaningful information representing user preferences. An original bookmark indicating only address information is categorized for merging semantic meanings by using public web directory services. These categorized bookmarks are expressed in a hierarchical tree structure. However, most current web directory services cannot afford to normalize and manage the topic hierarchy. There are several kinds of structural incompleteness such as multiple references and heterogeneous tree structures. In order to extract user prefer-ences, this paper proposes a method for driving these problems and the influ-ence propagation methods based on Bayesian networks. Therefore, the preference maps representing users’ interests are also established as tree structures. With respect to the user clustering, an approximate tree matching method is used for mapping (overlapping) users’ preference maps. It is possible to make queries and process them efficiently according to categories. Finally, this paper is applied to implement collaborative web browsing that can guide and explore the web efficiently and adaptively.} }

%0 = inproceedings %A = Jung, Jason J. and Yoon, Jeong-Seob and Jo, GeunSik %B = INAP %D = 2001 %T = Collaborative Information Filtering by Using Categorized Bookmarks on the Web %U = jung01.ps

The World Wide Web has become a source of an enormous amount of information. Most Web browsers feature bookmarking facilities as a means to harness the vast Web space. Users record the URLs of the sites for future visits with bookmarks, but the organization and maintenance of the bookmark file costs users time and cognitive work. A personal agent is an automated program to which users can delegate often tedious or sophisticated tasks. We implemented a learning agent called BClassifier using the naive Bayesian learning method and we present our findings in this paper

@inproceedings{kim2001personal, author = {Kim, In-Cheol}, title = {A personal agent for bookmark classification}, editor = {M, Yuan S-T; Yokoo}, booktitle = {Intelligent Agents: Specification, Modeling, and Applications. 4th Pacific Rim International Workshop on Multi-Agents, PRIMA 2001. Proceedings (Lecture Notes in Artificial Intelligence Vol.2132)}, publisher = {Springer-Verlag}, address = {Dept. of Comput. Sci., Kyonggi Univ., Suwon, South Korea}, year = {2001}, pages = {210--21}, url = {link.springer.de/link/service/series/0558/bibs/2132/21320210.htm}, keywords = {studienarbeit, bookmark_classification, www, closely_related}, abstract = {The World Wide Web has become a source of an enormous amount of information. Most Web browsers feature bookmarking facilities as a means to harness the vast Web space. Users record the URLs of the sites for future visits with bookmarks, but the organization and maintenance of the bookmark file costs users time and cognitive work. A personal agent is an automated program to which users can delegate often tedious or sophisticated tasks. We implemented a learning agent called BClassifier using the naive Bayesian learning method and we present our findings in this paper} }

%0 = inproceedings %A = Kim, In-Cheol %B = Intelligent Agents: Specification, Modeling, and Applications. 4th Pacific Rim International Workshop on Multi-Agents, PRIMA 2001. Proceedings (Lecture Notes in Artificial Intelligence Vol.2132) %C = Dept. of Comput. Sci., Kyonggi Univ., Suwon, South Korea %D = 2001 %I = Springer-Verlag %T = A personal agent for bookmark classification %U = link.springer.de/link/service/series/0558/bibs/2132/21320210.htm

This paper reports on an ongoing development of an application that aims at identifying communities of use in the context of an organized group of people. The described application, called CoWing consists on mining users bookmark files in order to identify communities that share the same information interests. The system is composed of a set of assistant agents, called WINGS, and a central agent that manages the users organization. A Wing agent observes the user behavior in order to learn the user bookmark classification strategy. A hybrid neural case-based reasoning incremental classifier is used for this purpose. Classification knowledge learned by an agent is then used to identify, for each folder in the local bookmark hierarchy, a community of users that share the same interests in the theme of that folder.

@misc{malek2001cooperating, author = {Malek, Maria and Kanawati, Rushed}, title = {A Cooperating Hybrid Neural-CBR Classifiers for Building On-line Communities}, year = {2001}, url = {malek01.ps}, keywords = {studienarbeit, closely_related}, abstract = {This paper reports on an ongoing development of an application that aims at identifying communities of use in the context of an organized group of people. The described application, called CoWing consists on mining users bookmark files in order to identify communities that share the same information interests. The system is composed of a set of assistant agents, called WINGS, and a central agent that manages the users organization. A Wing agent observes the user behavior in order to learn the user bookmark classification strategy. A hybrid neural case-based reasoning incremental classifier is used for this purpose. Classification knowledge learned by an agent is then used to identify, for each folder in the local bookmark hierarchy, a community of users that share the same interests in the theme of that folder.} }

%0 = misc %A = Malek, Maria and Kanawati, Rushed %B = } %C = %D = 2001 %I = %T = A Cooperating Hybrid Neural-CBR Classifiers for Building On-line Communities} %U = malek01.ps

Bookmark systems are now recognised as a practical mean that allow users to land mark interesting sites in the huge information space that constitute the World Wide Web. In this paper we argue that, by building collaborative bookmark management tools where a group of people can share their experiences and their results in feeding and organising personal bookmark sets, bookmarks can be transformed into effective customized web spaces. In this paper we first present a study of main requirements that a shared bookmark system should meet. Then the design space of such applications is analysed. The set of identified requirements is used to compare and criticise main collaborative shared bookmark systems that are proposed in the literature. Main drawbacks of existing systems are a) the weak customisation of shared spaces, b) the lack of efficient and easy to use privacy protection policies, and c) the adoption of centralised architectures that affects badly responsiveness, availability and d...

@inproceedings{kanawati2000informing, author = {Kanawati, R. and Malek, M.}, title = {Informing the design of shared bookmark systems}, booktitle = {Proceedings of the International Conference on Computer Assisted Information Retrieval (RIAO)}, address = {Paris, France}, year = {2000}, url = {citeseer.ist.psu.edu/kanawati00informing.html}, keywords = {closely_related, studienarbeit}, abstract = {Bookmark systems are now recognised as a practical mean that allow users to land mark interesting sites in the huge information space that constitute the World Wide Web. In this paper we argue that, by building collaborative bookmark management tools where a group of people can share their experiences and their results in feeding and organising personal bookmark sets, bookmarks can be transformed into effective customized web spaces. In this paper we first present a study of main requirements that a shared bookmark system should meet. Then the design space of such applications is analysed. The set of identified requirements is used to compare and criticise main collaborative shared bookmark systems that are proposed in the literature. Main drawbacks of existing systems are a) the weak customisation of shared spaces, b) the lack of efficient and easy to use privacy protection policies, and c) the adoption of centralised architectures that affects badly responsiveness, availability and d...} }

%0 = inproceedings %A = Kanawati, R. and Malek, M. %B = Proceedings of the International Conference on Computer Assisted Information Retrieval (RIAO) %C = Paris, France %D = 2000 %T = Informing the design of shared bookmark systems %U = citeseer.ist.psu.edu/kanawati00informing.html

The objective of the SELECT project is to help Internet users find the most reliable, valuable, important and interesting information quickly and easily, hence reducing information overload. In these ways, SELECT will make a positive contribution to the problem of helping users tailor their information environments to meet their individual needs. The approach adopted in SELECT is to develop a general architecture for information filtering and recommendation systems, and to use this to implement and evaluate different strategies and techniques. In this paper we describe GroupMark, a prototype of a SELECT-based social recommendation tool for the WWW that is based upon shared bookmarks. We focus in particular on how GroupMark seeks to combine content-based and collaborative filtering techniques, and on the user interface issues raised by recommendation tools: i.e., the mechanisms for controlling behaviour and the visualisation of results.

@inproceedings{pemberton2000groupmark, author = {Pemberton, Duncan and Rodden, Tom and Procter, Rob}, title = {GroupMark: A WWW Recommender System Combining Collaborative and Information Filtering}, booktitle = {Proceedings of the 6th ERCIM Workshop on 'User Interfaces for All'}, series = {Long Papers}, publisher = {ERCIM}, year = {2000}, number = {12}, pages = {13}, url = {ui4all.ics.forth.gr/UI4ALL-2000/files/Long_papers/Pemberton.pdf}, keywords = {studienarbeit, closely_related}, abstract = {The objective of the SELECT project is to help Internet users find the most reliable, valuable, important and interesting information quickly and easily, hence reducing information overload. In these ways, SELECT will make a positive contribution to the problem of helping users tailor their information environments to meet their individual needs. The approach adopted in SELECT is to develop a general architecture for information filtering and recommendation systems, and to use this to implement and evaluate different strategies and techniques. In this paper we describe GroupMark, a prototype of a SELECT-based social recommendation tool for the WWW that is based upon shared bookmarks. We focus in particular on how GroupMark seeks to combine content-based and collaborative filtering techniques, and on the user interface issues raised by recommendation tools: i.e., the mechanisms for controlling behaviour and the visualisation of results.} }

%0 = inproceedings %A = Pemberton, Duncan and Rodden, Tom and Procter, Rob %B = Proceedings of the 6th ERCIM Workshop on 'User Interfaces for All' %D = 2000 %I = ERCIM %T = GroupMark: A WWW Recommender System Combining Collaborative and Information Filtering %U = ui4all.ics.forth.gr/UI4ALL-2000/files/Long_papers/Pemberton.pdf

We extend the notion of bookmark management by introducing the functionali- ties of hypermedia databases. PowerBookmarks is a Web information organization, sharing, and management tool, which parses metadata from bookmarked URLs and uses it to index and classify the URLs. PowerBookmarks supports advanced query, classification, and navigation functionalities on collections of bookmarks. Power- Bookmarks monitors and utilizes users' access patterns to provide many useful per- sonalized services, such as automated URL bookmarking, document refreshing, and bookmark expiration. It also allows users to specify their preference in bookmark management, such as ranking schemes and classification tree structures. Subscrip- tion services for new or updated documents of users' interests are also supported.

@inproceedings{li1999powerbookmarks, author = {Li, W. and Vu, Q. and Chang, E. and Agrawal, D. and Hara, Y. and Takano, H.}, title = {PowerBookmarks: A System for Personalizable Web Information Organization}, booktitle = {Proceedings of the Eighth International World-Wide Web Conference}, year = {1999}, url = {li99b.ps}, keywords = {studienarbeit, personalization, navigation, classification, www, closely_related}, abstract = {We extend the notion of bookmark management by introducing the functionali- ties of hypermedia databases. PowerBookmarks is a Web information organization, sharing, and management tool, which parses metadata from bookmarked URLs and uses it to index and classify the URLs. PowerBookmarks supports advanced query, classification, and navigation functionalities on collections of bookmarks. Power- Bookmarks monitors and utilizes users' access patterns to provide many useful per- sonalized services, such as automated URL bookmarking, document refreshing, and bookmark expiration. It also allows users to specify their preference in bookmark management, such as ranking schemes and classification tree structures. Subscrip- tion services for new or updated documents of users' interests are also supported.} }

%0 = inproceedings %A = Li, W. and Vu, Q. and Chang, E. and Agrawal, D. and Hara, Y. and Takano, H. %B = Proceedings of the Eighth International World-Wide Web Conference %D = 1999 %T = PowerBookmarks: A System for Personalizable Web Information Organization %U = li99b.ps

Users of the Web are overloaded with information. This medium is "polluted" with redundant, erroneous and low quality information. A WWW survey of 11,700 users conducted from April 10 to May 10, 1996[1] indicates that 30.31% of the users report "finding known info" is their problem and 27.80% of the users report organizing collected information as their problem. An empirical study[2] on users' revisitation patterns to WWW pages found that 58% of an individual's pages are revisits. With these study results, we believe the Web users would like to build and organize a larger collection of bookmarks for future references than they can reasonably maintain now.

@inproceedings{li1999powerbookmarksa, author = {Li, Wen-Syan and Vu, Quoc and Chang, Edward and Agrawal, Divyakant and Hirata, Kyoji and Mukherjea, Sougata and Wu, Yi-Leh and Bufi, Corey and Chang, Chen-Chuan Kevin and Hara, Yoshinori and Ito, Reiko and Kimura, Yutaka and Shimazu, Kezuyuki and Saito, Yukiyoshi}, title = {PowerBookmarks: a system for personalizable Web information organization, sharing, and management}, booktitle = {SIGMOD '99: Proceedings of the 1999 ACM SIGMOD international conference on Management of data}, publisher = {ACM Press}, address = {New York, NY, USA}, year = {1999}, pages = {565--567}, url = {doi.acm.org/10.1145/304182.304578}, keywords = {studienarbeit, closely_related}, abstract = {Users of the Web are overloaded with information. This medium is "polluted" with redundant, erroneous and low quality information. A WWW survey of 11,700 users conducted from April 10 to May 10, 1996[1] indicates that 30.31% of the users report "finding known info" is their problem and 27.80% of the users report organizing collected information as their problem. An empirical study[2] on users' revisitation patterns to WWW pages found that 58% of an individual's pages are revisits. With these study results, we believe the Web users would like to build and organize a larger collection of bookmarks for future references than they can reasonably maintain now.} }

%0 = inproceedings %A = Li, Wen-Syan and Vu, Quoc and Chang, Edward and Agrawal, Divyakant and Hirata, Kyoji and Mukherjea, Sougata and Wu, Yi-Leh and Bufi, Corey and Chang, Chen-Chuan Kevin and Hara, Yoshinori and Ito, Reiko and Kimura, Yutaka and Shimazu, Kezuyuki and Saito, Yukiyoshi %B = SIGMOD '99: Proceedings of the 1999 ACM SIGMOD international conference on Management of data %C = New York, NY, USA %D = 1999 %I = ACM Press %T = PowerBookmarks: a system for personalizable Web information organization, sharing, and management %U = doi.acm.org/10.1145/304182.304578

Web browser bookmarking facilities predominate as the method of choice for managing URLs. In this paper, we describe some deficiencies of current bookmarking schemes, and examine an alternative to current approaches. We present WebTaggerTM, an implemented prototype of a personal bookmarking service that provides both individuals and groups with a customizable means of organizing and accessing Web-based information resources. In addition, the service enables users to supply feedback on the utility of these resources relative to their information needs, and provides dynamically-updated ranking of resources based on incremental user feedback. Individuals may access the service from anywhere on the Internet, and require no special software. This service greatly simplifies the process of sharing URLs within groups, in comparison with manual methods involving email. The underlying bookmark organization scheme is more natural and flexible than current hierarchical schemes supported by the major Web browsers, and enables rapid access to stored bookmarks.

@article{keller1997bookmarking, author = {Keller, Richard M. and Wolfe, Shawn and Chen, James R. and Rabinowitz, Joshua L. and Mathe, Nathalie}, title = {A Bookmarking Service for Organizing and Sharing URLs.}, journal = {Computer Networks}, year = {1997}, volume = {29}, number = {8-13}, pages = {1103-1114}, note = {bibsource: DBLP, http://dblp.uni-trier.de}, url = {dx.doi.org/10.1016/S0169-7552(97)00028-7}, keywords = {closely_related, studienarbeit}, abstract = {Web browser bookmarking facilities predominate as the method of choice for managing URLs. In this paper, we describe some deficiencies of current bookmarking schemes, and examine an alternative to current approaches. We present WebTaggerTM, an implemented prototype of a personal bookmarking service that provides both individuals and groups with a customizable means of organizing and accessing Web-based information resources. In addition, the service enables users to supply feedback on the utility of these resources relative to their information needs, and provides dynamically-updated ranking of resources based on incremental user feedback. Individuals may access the service from anywhere on the Internet, and require no special software. This service greatly simplifies the process of sharing URLs within groups, in comparison with manual methods involving email. The underlying bookmark organization scheme is more natural and flexible than current hierarchical schemes supported by the major Web browsers, and enables rapid access to stored bookmarks.} }

%0 = article %A = Keller, Richard M. and Wolfe, Shawn and Chen, James R. and Rabinowitz, Joshua L. and Mathe, Nathalie %D = 1997 %T = A Bookmarking Service for Organizing and Sharing URLs. %U = dx.doi.org/10.1016/S0169-7552(97)00028-7

The explosive growth in the Web leads to the need for personalized client-based local URL repositories often called bookmarks. We present a novel approach to bookmark organization that provides automatic classification together with user adaption.

@inproceedings{mareek1996automatically, author = {Mareek, Yoelle S. and Shaul, Israel Z. Ben}, title = {Automatically Organizing Bookmarks per Contents}, booktitle = {Proceedings of the fifth international World Wide Web conference on Computer networks and ISDN systems}, publisher = {Elsevier Science Publishers B. V.}, address = {Amsterdam, The Netherlands}, year = {1996}, pages = {1321 -- 1333}, url = {http://www.w3.org/Conferences/WWW5/fich_html/paper-sessions.html}, keywords = {studienarbeit, closely_related}, abstract = {The explosive growth in the Web leads to the need for personalized client-based local URL repositories often called bookmarks. We present a novel approach to bookmark organization that provides automatic classification together with user adaption.} }

%0 = inproceedings %A = Mareek, Yoelle S. and Shaul, Israel Z. Ben %B = Proceedings of the fifth international World Wide Web conference on Computer networks and ISDN systems %C = Amsterdam, The Netherlands %D = 1996 %I = Elsevier Science Publishers B. V. %T = Automatically Organizing Bookmarks per Contents %U = http://www.w3.org/Conferences/WWW5/fich_html/paper-sessions.html