QuickSearch:   Number of matching entries: 0.

Search Settings

    AuthorTitleYearJournal/ProceedingsReftypeDOI/URL
    Doerfel, S., Zoller, D., Singer, P., Niebler, T., Hotho, A. & Strohmaier, M. Of course we share! Testing Assumptions about Social Tagging Systems 2014   techreport URL 
    Abstract: Social tagging systems have established themselves as an important part in
    day's web and have attracted the interest from our research community in a
    riety of investigations. The overall vision of our community is that simply
    rough interactions with the system, i.e., through tagging and sharing of
    sources, users would contribute to building useful semantic structures as
    ll as resource indexes using uncontrolled vocabulary not only due to the
    sy-to-use mechanics. Henceforth, a variety of assumptions about social
    gging systems have emerged, yet testing them has been difficult due to the
    sence of suitable data. In this work we thoroughly investigate three
    ailable assumptions - e.g., is a tagging system really social? - by examining
    ve log data gathered from the real-world public social tagging system
    bSonomy. Our empirical results indicate that while some of these assumptions
    ld to a certain extent, other assumptions need to be reflected and viewed in
    very critical light. Our observations have implications for the design of
    ture search and other algorithms to better reflect the actual user behavior.
    BibTeX:
    @techreport{doerfel2014course,
      author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus},
      title = {Of course we share! Testing Assumptions about Social Tagging Systems},
      year = {2014},
      note = {cite arxiv:1401.0629},
      url = {http://arxiv.org/abs/1401.0629}
    }
    
    Duarte Torres, S., Weber, I. & Hiemstra, D. Analysis of Search and Browsing Behavior of Young Users on the Web 2014 ACM Transactions on the Web
    Vol. 8(2), pp. 7:1-7:54 
    article DOI URL 
    Abstract: The Internet is increasingly used by young children for all kinds of purposes. Nonetheless, there are not many resources especially designed for children on the Internet and most of the content online is designed for grown-up users. This situation is problematic if we consider the large differences between young users and adults since their topic interests, computer skills, and language capabilities evolve rapidly during childhood. There is little research aimed at exploring and measuring the difficulties that children encounter on the Internet when searching for information and browsing for content. In the first part of this work, we employed query logs from a commercial search engine to quantify the difficulties children of different ages encounter on the Internet and to characterize the topics that they search for. We employed query metrics (e.g., the fraction of queries posed in natural language), session metrics (e.g., the fraction of abandoned sessions), and click activity (e.g., the fraction of ad clicks). The search logs were also used to retrace stages of child development. Concretely, we looked for changes in interests (e.g., the distribution of topics searched) and language development (e.g., the readability of the content accessed and the vocabulary size). In the second part of this work, we employed toolbar logs from a commercial search engine to characterize the browsing behavior of young users, particularly to understand the activities on the Internet that trigger search. We quantified the proportion of browsing and search activity in the toolbar sessions and we estimated the likelihood of a user to carry out search on the Web vertical and multimedia verticals (i.e., videos and images) given that the previous event is another search event or a browsing event. We observed that these metrics clearly demonstrate an increased level of confusion and unsuccessful search sessions among children. We also found a clear relation between the reading level of the clicked pages and characteristics of the users such as age and educational attainment. In terms of browsing behavior, children were found to start their activities on the Internet with a search engine (instead of directly browsing content) more often than adults. We also observed a significantly larger amount of browsing activity for the case of teenager users. Interestingly we also found that if children visit knowledge-related Web sites (i.e., information-dense pages such as Wikipedia articles), they subsequently do more Web searches than adults. Additionally, children and especially teenagers were found to have a greater tendency to engage in multimedia search, which calls to improve the aggregation of multimedia results into the current search result pages.
    BibTeX:
    @article{duartetorres2014analysis,
      author = {Duarte Torres, Sergio and Weber, Ingmar and Hiemstra, Djoerd},
      title = {Analysis of Search and Browsing Behavior of Young Users on the Web},
      journal = {ACM Transactions on the Web},
      publisher = {ACM},
      year = {2014},
      volume = {8},
      number = {2},
      pages = {7:1--7:54},
      url = {http://doi.acm.org/10.1145/2555595},
      doi = {http://dx.doi.org/10.1145/2555595}
    }
    
    Agosti, M., Crivellari, F. & Di Nunzio, G. Web log analysis: a review of a decade of studies about information acquisition, inspection and interpretation of user interaction 2012 Data Mining and Knowledge Discovery
    Vol. 24(3), pp. 663-696 
    article DOI URL 
    Abstract: In the last decade, the importance of analyzing information management systems logs has grown, because log data constitute a relevant aspect in evaluating the quality of such systems. A review of 10 years of research on log analysis is presented in this paper. About 50 papers and posters from five major conferences and about 30 related journal papers have been selected to trace the history of the state-of-the-art in this field. The paper presents an overview of two main themes: Web search engine log analysis and Digital Library System log analysis. The problem of the analysis of different sources of log data and the distribution of data are investigated.
    BibTeX:
    @article{agosti2012analysis,
      author = {Agosti, Maristella and Crivellari, Franco and Di Nunzio, GiorgioMaria},
      title = {Web log analysis: a review of a decade of studies about information acquisition, inspection and interpretation of user interaction},
      journal = {Data Mining and Knowledge Discovery},
      publisher = {Springer US},
      year = {2012},
      volume = {24},
      number = {3},
      pages = {663-696},
      url = {http://dx.doi.org/10.1007/s10618-011-0228-8},
      doi = {http://dx.doi.org/10.1007/s10618-011-0228-8}
    }
    
    Strohmaier, M., Körner, C. & Kern, R. Understanding why users tag: A survey of tagging motivation literature and results from an empirical study 2012 Web Semantics: Science, Services and Agents on the World Wide Web
    Vol. 17(0), pp. 1 - 11 
    article DOI URL 
    Abstract: While recent progress has been achieved in understanding the structure and dynamics of social tagging systems, we know little about the underlying user motivations for tagging, and how they influence resulting folksonomies and tags. This paper addresses three issues related to this question. (1) What distinctions of user motivations are identified by previous research, and in what ways are the motivations of users amenable to quantitative analysis? (2) To what extent does tagging motivation vary across different social tagging systems? (3) How does variability in user motivation influence resulting tags and folksonomies? In this paper, we present measures to detect whether a tagger is primarily motivated by categorizing or describing resources, and apply these measures to datasets from seven different tagging systems. Our results show that (a) users’ motivation for tagging varies not only across, but also within tagging systems, and that (b) tag agreement among users who are motivated by categorizing resources is significantly lower than among users who are motivated by describing resources. Our findings are relevant for (1) the development of tag-based user interfaces, (2) the analysis of tag semantics and (3) the design of search algorithms for social tagging systems.
    BibTeX:
    @article{strohmaier2012understanding,
      author = {Strohmaier, Markus and Körner, Christian and Kern, Roman},
      title = {Understanding why users tag: A survey of tagging motivation literature and results from an empirical study},
      journal = {Web Semantics: Science, Services and Agents on the World Wide Web},
      year = {2012},
      volume = {17},
      number = {0},
      pages = {1 - 11},
      url = {http://www.sciencedirect.com/science/article/pii/S1570826812000820},
      doi = {http://dx.doi.org/10.1016/j.websem.2012.09.003}
    }
    
    Carman, M.J., Baillie, M., Gwadera, R. & Crestani, F. A statistical comparison of tag and query logs 2009 Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval, pp. 123-130  inproceedings DOI URL 
    Abstract: We investigate tag and query logs to see if the terms people use to annotate websites are similar to the ones they use to query for them. Over a set of URLs, we compare the distribution of tags used to annotate each URL with the distribution of query terms for clicks on the same URL. Understanding the relationship between the distributions is important to determine how useful tag data may be for improving search results and conversely, query data for improving tag prediction. In our study, we compare both term frequency distributions using vocabulary overlap and relative entropy. We also test statistically whether the term counts come from the same underlying distribution. Our results indicate that the vocabulary used for tagging and searching for content are similar but not identical. We further investigate the content of the websites to see which of the two distributions (tag or query) is most similar to the content of the annotated/searched URL. Finally, we analyze the similarity for different categories of URLs in our sample to see if the similarity between distributions is dependent on the topic of the website or the popularity of the URL.
    BibTeX:
    @inproceedings{carman2009statistical,
      author = {Carman, Mark J. and Baillie, Mark and Gwadera, Robert and Crestani, Fabio},
      title = {A statistical comparison of tag and query logs},
      booktitle = {Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval},
      publisher = {ACM},
      year = {2009},
      pages = {123--130},
      url = {http://doi.acm.org/10.1145/1571941.1571965},
      doi = {http://dx.doi.org/10.1145/1571941.1571965}
    }
    
    Huntington, P., Nicholas, D. & Jamali, H.R. Website usage metrics: A re-assessment of session data 2008 Information Processing & Management
    Vol. 44(1), pp. 358 - 372 
    article DOI URL 
    Abstract: Metrics derived from user visits or sessions provide a means of evaluating Websites and an important insight into online information seeking behaviour, the most important of them being the duration of sessions and the number of pages viewed in a session, a possible busyness indicator. However, the identification of session (termed often ‘sessionization’) is fraught with difficulty in that there is no way of determining from a transactional log file that a user has ended their session. No one logs out. Instead a session delimiter has to be applied and this is typically done on the basis of a standard period of inactivity. To date researchers have discussed the issue of a time out delimiter in terms of a single value and if a page view time exceeds the cut-off value the session is deemed to have ended. This approach assumes that page view time is a single distribution and that the cut-off value is one point on that distribution. The authors however argue that page time distribution is composed of a number of quite separate view time distributions because of the marked differences in view times between pages (abstract, contents page, full text). This implies that a number of timeout delimiters should be applied. Employing data from a study of the OhioLINK digital journal library, the authors demonstrate how the setting of a time out delimiter impacts on the estimate of page view time and the number of estimated session. Furthermore, they also show how a number of timeout delimiters might apply and they argue that this gives a better and more robust estimate of the number of sessions, session time and page view time compared to an application of a single timeout delimiter.
    BibTeX:
    @article{huntington2008website,
      author = {Huntington, Paul and Nicholas, David and Jamali, Hamid R.},
      title = {Website usage metrics: A re-assessment of session data},
      journal = {Information Processing & Management},
      year = {2008},
      volume = {44},
      number = {1},
      pages = {358 - 372},
      note = {Evaluation of Interactive Information Retrieval Systems},
      url = {http://www.sciencedirect.com/science/article/pii/S0306457307000817},
      doi = {http://dx.doi.org/10.1016/j.ipm.2007.03.003}
    }
    
    Sinclair, J. & Cardew-Hall, M. The folksonomy tag cloud: when is it useful? 2008 Journal of Information Science
    Vol. 34(1), pp. 15-29 
    article DOI URL 
    Abstract:
    he weighted list, known popularly as a `tag cloud', has appeared on many popular folksonomy-based web-sites. Flickr, Delicious, Technorati and many others have all featured a tag cloud at some point in their history. However, it is unclear whether the tag cloud is actually useful as an aid to finding information. We conducted an experiment, giving participants the option of using a tag cloud or a traditional search interface to answer various questions. We found that where the information-seeking task required specific information, participants preferred the search interface. Conversely, where the information-seeking task was more general, participants preferred the tag cloud. While the tag cloud is not without value, it is not sufficient as the sole means of navigation for a folksonomy-based dataset.
    BibTeX:
    @article{sinclair2008folksonomy,
      author = {Sinclair, James and Cardew-Hall, Michael},
      title = {The folksonomy tag cloud: when is it useful?},
      journal = {Journal of Information Science},
      year = {2008},
      volume = {34},
      number = {1},
      pages = {15-29},
      url = {http://jis.sagepub.com/content/34/1/15.abstract},
      doi = {http://dx.doi.org/10.1177/0165551506078083}
    }
    
    Nicholas, D., Huntington, P. & Jamali, H.R. Diversity in the Information Seeking Behaviour of the Virtual Scholar: Institutional Comparisons 2007 The Journal of Academic Librarianship
    Vol. 33(6), pp. 629 - 638 
    article DOI URL 
    Abstract: The logs of four universities using the OhioLINK journal system were evaluated for a period of fifteen months using deep log analysis methods in order to compare and contrast the information seeking behaviour of their users. Large differences were found, especially between the research and teaching universities. Methodological problems associated with making the comparisons are discussed in some detail especially in terms of defining online sessions.
    BibTeX:
    @article{nicholas2007diversity,
      author = {Nicholas, David and Huntington, Paul and Jamali, Hamid R.},
      title = {Diversity in the Information Seeking Behaviour of the Virtual Scholar: Institutional Comparisons},
      journal = {The Journal of Academic Librarianship},
      year = {2007},
      volume = {33},
      number = {6},
      pages = {629 - 638},
      url = {http://www.sciencedirect.com/science/article/pii/S0099133307001759},
      doi = {http://dx.doi.org/10.1016/j.acalib.2007.09.001}
    }
    
    Voss, J. Tagging, Folksonomy & Co - Renaissance of Manual Indexing? 2007   misc URL 
    Abstract: This paper gives an overview of current trends in manual indexing on the Web.
    ong with a general rise of user generated content there are more and more
    gging systems that allow users to annotate digital resources with tags
    eywords) and share their annotations with other users. Tagging is frequently
    en in contrast to traditional knowledge organization systems or as something
    mpletely new. This paper shows that tagging should better be seen as a
    pular form of manual indexing on the Web. Difference between controlled and
    ee indexing blurs with sufficient feedback mechanisms. A revised typology of
    gging systems is presented that includes different user roles and knowledge
    ganization systems with hierarchical relationships and vocabulary control. A
    tailed bibliography of current research in collaborative tagging is included.
    BibTeX:
    @misc{voss2007tagging,
      author = {Voss, Jakob},
      title = {Tagging, Folksonomy & Co - Renaissance of Manual Indexing?},
      year = {2007},
      note = {cite arxiv:cs/0701072Comment: Preprint. 12 pages, 1 figure, 54 references},
      url = {http://arxiv.org/abs/cs/0701072}
    }
    
    Iváncsy, R. & Vajk, I. Frequent Pattern Mining in Web Log Data 2006 Acta Polytechnica Hungarica
    Vol. 3(1) 
    article URL 
    Abstract: Abstract: Frequent pattern mining is a heavily researched area in the field of data mining with wide range of applications. One of them is to use frequent pattern discovery methods in Web log data. Discovering hidden information from Web log data is called Web usage mining. The aim of discovering frequent patterns in Web log data is to obtain information about the navigational behavior of the users. This can be used for advertising purposes, for creating dynamic user profiles etc. In this paper three pattern mining approaches are investigated from the Web usage mining point of view. The different patterns in Web log mining are page sets, page sequences and page graphs.
    BibTeX:
    @article{ivncsy2006frequent,
      author = {Iváncsy, Renáta and Vajk, István},
      title = {Frequent Pattern Mining in Web Log Data},
      journal = {Acta Polytechnica Hungarica},
      year = {2006},
      volume = {3},
      number = {1},
      url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.101.4559}
    }
    
    Jansen, B.J. Search log analysis: What it is, what's been done, how to do it 2006 Library & Information Science Research
    Vol. 28(3), pp. 407 - 432 
    article DOI URL 
    Abstract: The use of data stored in transaction logs of Web search engines, Intranets, and Web sites can provide valuable insight into understanding the information-searching process of online searchers. This understanding can enlighten information system design, interface development, and devising the information architecture for content collections. This article presents a review and foundation for conducting Web search transaction log analysis. A methodology is outlined consisting of three stages, which are collection, preparation, and analysis. The three stages of the methodology are presented in detail with discussions of goals, metrics, and processes at each stage. Critical terms in transaction log analysis for Web searching are defined. The strengths and limitations of transaction log analysis as a research method are presented. An application to log client-side interactions that supplements transaction logs is reported on, and the application is made available for use by the research community. Suggestions are provided on ways to leverage the strengths of, while addressing the limitations of, transaction log analysis for Web-searching research. Finally, a complete flat text transaction log from a commercial search engine is available as supplementary material with this manuscript.
    BibTeX:
    @article{jansen2006search,
      author = {Jansen, Bernard J.},
      title = {Search log analysis: What it is, what's been done, how to do it},
      journal = {Library & Information Science Research},
      year = {2006},
      volume = {28},
      number = {3},
      pages = {407 - 432},
      url = {http://www.sciencedirect.com/science/article/pii/S0740818806000673},
      doi = {http://dx.doi.org/10.1016/j.lisr.2006.06.005}
    }
    
    Nicholas, D., Huntington, P. & Watkinson, A. Scholarly journal usage: the results of deep log analysis 2005 Journal of Documentation
    Vol. 61(2), pp. 248-280 
    article URL 
    BibTeX:
    @article{nicholas2005scholarly,
      author = {Nicholas, David and Huntington, Paul and Watkinson, Anthony},
      title = {Scholarly journal usage: the results of deep log analysis},
      journal = {Journal of Documentation},
      publisher = {Emerald Group Publishing Limited},
      year = {2005},
      volume = {61},
      number = {2},
      pages = {248--280},
      url = {http://www.emeraldinsight.com/journals.htm?articleid=1465024&show=abstract}
    }
    
    Park, S., Lee, J.H. & Bae, H.J. End user searching: A Web log analysis of NAVER, a Korean Web search engine 2005 Library & Information Science Research
    Vol. 27(2), pp. 203 - 221 
    article DOI URL 
    Abstract: Transaction logs of NAVER, a major Korean Web search engine, were analyzed to track the information-seeking behavior of Korean Web users. These transaction logs include more than 40 million queries collected over 1 week. This study examines current transaction log analysis methodologies and proposes a method for log cleaning, session definition, and query classification. A term definition method which is necessary for Korean transaction log analysis is also discussed. The results of this study show that users behave in a simple way: they type in short queries with a few query terms, seldom use advanced features, and view few results' pages. Users also behave in a passive way: they seldom change search environments set by the system. It is of interest that users tend to change their queries totally rather than adding or deleting terms to modify the previous queries. The results of this study might contribute to the development of more efficient and effective Web search engines and services.
    BibTeX:
    @article{park2005searching,
      author = {Park, Soyeon and Lee, Joon Ho and Bae, Hee Jin},
      title = {End user searching: A Web log analysis of NAVER, a Korean Web search engine},
      journal = {Library & Information Science Research},
      year = {2005},
      volume = {27},
      number = {2},
      pages = {203 - 221},
      url = {http://www.sciencedirect.com/science/article/pii/S0740818805000083},
      doi = {http://dx.doi.org/10.1016/j.lisr.2005.01.013}
    }
    
    Suneetha, K.R. & Krishnamoorthy, K.R. Identifying User Behavior by Analyzing Web Server Access Log File 2005 International Journal of Computer Science and Network Security
    Vol. 9(4), pp. 327-332 
    article  
    BibTeX:
    @article{suneetha2005identifying,
      author = {Suneetha, K. R. and Krishnamoorthy, K. R.},
      title = {Identifying User Behavior by Analyzing Web Server 
    cess Log File}, journal = {International Journal of Computer Science and Network Security}, year = {2005}, volume = {9}, number = {4}, pages = {327-332} }
    Weinberger, D. Tagging and Why it Matters 2005 SSRN eLibrary  article DOI  
    BibTeX:
    @article{weinberger2005tagging,
      author = {Weinberger, David},
      title = {Tagging and Why it Matters},
      journal = {SSRN eLibrary},
      publisher = {SSRN},
      year = {2005},
      doi = {http://dx.doi.org/10.2139/ssrn.870594}
    }
    
    Rose, D.E. & Levinson, D. Understanding user goals in web search 2004 Proceedings of the 13th international conference on World Wide Web, pp. 13-19  inproceedings DOI URL 
    Abstract: Previous work on understanding user web search behavior has focused on how people search and what they are searching for, but not why they are searching. In this paper, we describe a framework for understanding the underlying goals of user searches, and our experience in using the framework to manually classify queries from a web search engine. Our analysis suggests that so-called navigational" searches are less prevalent than generally believed while a previously unexplored "resource-seeking" goal may account for a large fraction of web searches. We also illustrate how this knowledge of user search goals might be used to improve future web search engines.
    BibTeX:
    @inproceedings{rose2004understanding,
      author = {Rose, Daniel E. and Levinson, Danny},
      title = {Understanding user goals in web search},
      booktitle = {Proceedings of the 13th international conference on World Wide Web},
      publisher = {ACM},
      year = {2004},
      pages = {13--19},
      url = {http://doi.acm.org/10.1145/988672.988675},
      doi = {http://dx.doi.org/10.1145/988672.988675}
    }
    
    Baglioni, M., Ferrara, U., Romei, A., Ruggieri, S. & Turini, F. Preprocessing and Mining Web Log Data for Web Personalization 2003
    Vol. 2829AI*IA 2003: Advances in Artificial Intelligence, pp. 237-249 
    incollection DOI URL 
    Abstract: We describe the web usage mining activities of an on-going project, called ClickWorld, that aims at extracting models of the navigational behaviour of a web site users. The models are inferred from the access logs of a web server by means of data and web mining techniques. The extracted knowledge is deployed to the purpose of offering a personalized and proactive view of the web services to users. We first describe the preprocessing steps on access logs necessary to clean, select and prepare data for knowledge extraction. Then we show two sets of experiments: the first one tries to predict the sex of a user based on the visited web pages, and the second one tries to predict whether a user might be interested in visiting a section of the site.
    BibTeX:
    @incollection{baglioni2003preprocessing,
      author = {Baglioni, M. and Ferrara, U. and Romei, A. and Ruggieri, S. and Turini, F.},
      title = {Preprocessing and Mining Web Log Data for Web Personalization},
      booktitle = {AI*IA 2003: Advances in Artificial Intelligence},
      publisher = {Springer Berlin Heidelberg},
      year = {2003},
      volume = {2829},
      pages = {237-249},
      url = {http://dx.doi.org/10.1007/978-3-540-39853-0_20},
      doi = {http://dx.doi.org/10.1007/978-3-540-39853-0_20}
    }
    
    Silverstein, C., Marais, H., Henzinger, M. & Moricz, M. Analysis of a very large web search engine query log 1999 SIGIR Forum
    Vol. 33(1), pp. 6-12 
    article DOI URL 
    Abstract: In this paper we present an analysis of an AltaVista Search Engine query log consisting of approximately 1 billion entries for search requests over a period of six weeks. This represents almost 285 million user sessions, each an attempt to fill a single information need. We present an analysis of individual queries, query duplication, and query sessions. We also present results of a correlation analysis of the log entries, studying the interaction of terms within queries. Our data supports the conjecture that web users differ significantly from the user assumed in the standard information retrieval literature. Specifically, we show that web users type in short queries, mostly look at the first 10 results only, and seldom modify the query. This suggests that traditional information retrieval techniques may not work well for answering web search requests. The correlation analysis showed that the most highly correlated items are constituents of phrases. This result indicates it may be useful for search engines to consider search terms as parts of phrases even if the user did not explicitly specify them as such.
    BibTeX:
    @article{silverstein1999analysis,
      author = {Silverstein, Craig and Marais, Hannes and Henzinger, Monika and Moricz, Michael},
      title = {Analysis of a very large web search engine query log},
      journal = {SIGIR Forum},
      publisher = {ACM},
      year = {1999},
      volume = {33},
      number = {1},
      pages = {6--12},
      url = {http://doi.acm.org/10.1145/331403.331405},
      doi = {http://dx.doi.org/10.1145/331403.331405}
    }
    
    Jones, S., Cunningham, S.J. & McNab, R. Usage analysis of a digital library 1998 Proceedings of the third ACM conference on Digital libraries, pp. 293-294  inproceedings DOI URL 
    BibTeX:
    @inproceedings{jones1998usage,
      author = {Jones, Steve and Cunningham, Sally Jo and McNab, Rodger},
      title = {Usage analysis of a digital library},
      booktitle = {Proceedings of the third ACM conference on Digital libraries},
      publisher = {ACM},
      year = {1998},
      pages = {293--294},
      url = {http://doi.acm.org/10.1145/276675.276739},
      doi = {http://dx.doi.org/10.1145/276675.276739}
    }
    

    Created by JabRef on 19/04/2024.