phone datasets. This area of research has emerged a decade ago, with the
increasing availability of large-scale anonymized datasets, and has grown into
a stand-alone topic. We will survey the contributions made so far on the social
networks that can be constructed with such data, the study of personal
mobility, geographical partitioning, urban planning, and help towards
development as well as security and privacy issues. ER - TY - CHAP AU - Piskorski, Jakub AU - Yangarber, Roman A2 - Poibeau, Thierry A2 - Saggion, Horacio A2 - Piskorski, Jakub A2 - Yangarber, Roman T1 - Information Extraction: Past, Present and Future T2 - Multi-source, Multilingual Information Extraction and Summarization PB - Springer Berlin Heidelberg C1 - PY - 2013/ VL - IS - SP - 23 EP - 49 UR - http://dx.doi.org/10.1007/978-3-642-28569-1_2 DO - 10.1007/978-3-642-28569-1_2 KW - extraction KW - information KW - sota KW - survey L1 - SN - 978-3-642-28568-4 N1 - Information Extraction: Past, Present and Future - Springer N1 - AB - In this chapter we present a brief overview of Information Extraction, which is an area of natural language processing that deals with finding factual information in free text. In formal terms, ER - TY - JOUR AU - Lü, Linyuan AU - Medo, Matúš AU - Yeung, Chi Ho AU - Zhang, Yi-Cheng AU - Zhang, Zi-Ke AU - Zhou, Tao T1 - Recommender systems JO - Physics Reports PY - 2012/ VL - 519 IS - 1 SP - 1 EP - 49 UR - http://www.sciencedirect.com/science/article/pii/S0370157312000828 DO - 10.1016/j.physrep.2012.02.006 KW - recommender KW - survey KW - toread L1 - SN - N1 - ScienceDirect.com - Physics Reports - Recommender systems N1 - AB - The ongoing rapid expansion of the Internet greatly increases the necessity of effective recommender systems for filtering the abundant information. Extensive research for recommender systems is conducted by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and practical achievements, unification and comparison of different approaches are lacking, which impedes further advances. In this article, we review recent developments in recommender systems and discuss the major challenges. We compare and evaluate available algorithms and examine their roles in the future developments. In addition to algorithms, physical aspects are described to illustrate macroscopic behavior of recommender systems. Potential impacts and future directions are discussed. We emphasize that recommendation has great scientific depth and combines diverse research fields which makes it interesting for physicists as well as interdisciplinary researchers. ER - TY - JOUR AU - Christin, Delphine AU - Reinhardt, Andreas AU - Kanhere, Salil S AU - Hollick, Matthias T1 - A survey on privacy in mobile participatory sensing applications JO - Journal of Systems and Software PY - 2011/ VL - 84 IS - 11 SP - 1928 EP - 1946 UR - http://scholar.google.de/scholar.bib?q=info:qpMZngbCBHYJ:scholar.google.com/&output=citation&scisig=AAGBfm0AAAAAVJLgOK6PYLcv_X2uOph4-evGd2AOVDax&scisf=4&hl=en&scfhb=1 DO - KW - everyaware KW - mobile KW - participatory KW - plattform KW - sensing KW - survey L1 - SN - N1 - N1 - AB - ER - TY - JOUR AU - Collobert, Ronan AU - Weston, Jason AU - Bottou, Léon AU - Karlen, Michael AU - Kavukcuoglu, Koray AU - Kuksa, Pavel P. T1 - Natural Language Processing (almost) from Scratch JO - CoRR PY - 2011/ VL - abs/1103.0398 IS - SP - EP - UR - http://static.googleusercontent.com/external_content/untrusted_dlcp/research.google.com/de//pubs/archive/35671.pdf DO - KW - nlp KW - survey KW - toread L1 - SN - N1 - N1 - AB - ER - TY - BOOK AU - A2 - Ricci, Francesco A2 - Rokach, Lior A2 - Shapira, Bracha A2 - Kantor, Paul B. T1 - Recommender Systems Handbook PB - Springer C1 - PY - 2011/ VL - IS - SP - EP - UR - http://dblp.uni-trier.de/db/reference/rsh/rsh2011.html DO - KW - ***** KW - handbook KW - overview KW - recommender KW - survey KW - systems L1 - SN - 978-0-387-85819-7 N1 - N1 - AB - ER - TY - JOUR AU - Herrera, Franciso AU - Carmona, Cristóbal AU - González, Pedro AU - del Jesus, María T1 - An overview on subgroup discovery: foundations and applications JO - Knowledge and Information Systems PY - 2010/ VL - IS - SP - 1 EP - 31 UR - http://dx.doi.org/10.1007/s10115-010-0356-2 DO - 10.1007/s10115-010-0356-2 KW - application KW - discovery KW - introduction KW - overview KW - subgroup KW - survey L1 - SN - N1 - SpringerLink - Knowledge and Information Systems, Online First™ N1 - AB - Subgroup discovery is a data mining technique which extracts interesting rules with respect to a target variable. An important characteristic of this task is the combination of predictive and descriptive induction. An overview related to the task of subgroup discovery is presented. This review focuses on the foundations, algorithms, and advanced studies together with the applications of subgroup discovery presented throughout the specialised bibliography. ER - TY - JOUR AU - Lane, N.D. AU - Miluzzo, E. AU - Lu, H. AU - Peebles, D. AU - Choudhury, T. AU - Campbell, A.T. T1 - A survey of mobile phone sensing JO - Communications Magazine, IEEE PY - 2010/ VL - 48 IS - 9 SP - 140 EP - 150 UR - DO - KW - everyaware KW - mobile KW - phone KW - sensing KW - survey L1 - SN - N1 - N1 - AB - ER - TY - JOUR AU - Liu, Bing T1 - Sentiment Analysis and Subjectivity JO - Handbook of Natural Language Processing PY - 2010/ VL - 2nd ed IS - SP - EP - UR - DO - KW - ***** KW - analysis KW - introduction KW - opinion KW - sentiment KW - survey L1 - SN - N1 - N1 - AB - ER - TY - JOUR AU - Alonso, S. AU - Cabrerizo, F.J. AU - Herrera-Viedma, E. AU - Herrera, F. T1 - h-Index: A review focused in its variants, computation and standardization for different scientific fields JO - Journal of Informetrics PY - 2009/ VL - 3 IS - 4 SP - 273 EP - 289 UR - http://www.sciencedirect.com/science/article/pii/S1751157709000339 DO - http://dx.doi.org/10.1016/j.joi.2009.04.001 KW - Informetrics KW - citation KW - h-Index KW - survey KW - toread L1 - SN - N1 - N1 - AB - ER - TY - GEN AU - Goldenberg, Anna AU - Zheng, Alice X AU - Fienberg, Stephen E AU - Airoldi, Edoardo M A2 - T1 - A survey of statistical network models JO - PB - C1 - PY - 2009/ VL - IS - SP - EP - UR - http://arxiv.org/abs/0912.5410 DO - KW - models KW - network KW - sota KW - survey KW - topic KW - toread L1 - N1 - A survey of statistical network models N1 - AB - Networks are ubiquitous in science and have become a focal point for
discussion in everyday life. Formal statistical models for the analysis of
network data have emerged as a major topic of interest in diverse areas of
study, and most of these involve a form of graphical representation.
Probability models on graphs date back to 1959. Along with empirical studies in
social psychology and sociology from the 1960s, these early works generated an
active network community and a substantial literature in the 1970s. This effort
moved into the statistical literature in the late 1970s and 1980s, and the past
decade has seen a burgeoning network literature in statistical physics and
computer science. The growth of the World Wide Web and the emergence of online
networking communities such as Facebook, MySpace, and LinkedIn, and a host of
more specialized professional network communities has intensified interest in
the study of networks and network data. Our goal in this review is to provide
the reader with an entry point to this burgeoning literature. We begin with an
overview of the historical development of statistical network modeling and then
we introduce a number of examples that have been studied in the network
literature. Our subsequent discussion focuses on a number of prominent static
and dynamic network models and their interconnections. We emphasize formal
model descriptions, and pay special attention to the interpretation of
parameters and their estimation. We end with a description of some open
problems and challenges for machine learning and statistics. ER - TY - GEN AU - Gunawardana, Asela AU - Shani, Guy A2 - T1 - A Survey of Accuracy Evaluation Metrics of Recommendation Tasks JO - PB - C1 - PY - 2009/ VL - v10 IS - SP - EP - UR - http://jmlr.csail.mit.edu/papers/v10/gunawardana09a.html DO - KW - evaluation KW - metrics KW - recommender KW - survey KW - toread L1 - N1 - N1 - AB - ER - TY - JOUR AU - Kolda, Tamara G. AU - Bader, Brett W. T1 - Tensor Decompositions and Applications. JO - SIAM Review PY - 2009/ VL - 51 IS - 3 SP - 455 EP - 500 UR - http://dblp.uni-trier.de/db/journals/siamrev/siamrev51.html#KoldaB09 DO - KW - decomposion KW - survey KW - tensor KW - toread L1 - SN - N1 - N1 - AB - ER - TY - BOOK AU - Staab, Steffen AU - Studer, Rudi A2 - T1 - Handbook on ontologies PB - Springer C1 - Berlin PY - 2009/ VL - IS - SP - EP - UR - http://public.eblib.com/choice/publicfullrecord.aspx?p=571805 DO - KW - handbook KW - ontology KW - sota KW - survey L1 - SN - 9783540926733 3540926739 N1 - Handbook on Ontologies N1 - AB - An ontology is a formal description of concepts and relationships that can exist for a community of human and/or machine agents. This book considers ontology languages, ontology engineering methods, example ontologies, infrastructures and technologies for ontologies, and how to bring this all into ontology-based infrastructures and applications. ER - TY - JOUR AU - Stamatatos, Efstathios T1 - A survey of modern authorship attribution methods JO - Journal of the American Society for Information Science and Technology PY - 2009/ VL - 60 IS - 3 SP - 538 EP - 556 UR - http://dx.doi.org/10.1002/asi.21001 DO - 10.1002/asi.21001 KW - DH KW - attribution KW - authorship KW - survey L1 - SN - N1 - A survey of modern authorship attribution methods - Stamatatos - 2008 - Journal of the American Society for Information Science and Technology - Wiley Online Library N1 - AB - Authorship attribution supported by statistical or computational methods has a long history starting from the 19th century and is marked by the seminal study of Mosteller and Wallace (1964) on the authorship of the disputed “Federalist Papers.” During the last decade, this scientific field has been developed substantially, taking advantage of research advances in areas such as machine learning, information retrieval, and natural language processing. The plethora of available electronic texts (e.g., e-mail messages, online forum messages, blogs, source code, etc.) indicates a wide variety of applications of this technology, provided it is able to handle short and noisy text from multiple candidate authors. In this article, a survey of recent advances of the automated approaches to attributing authorship is presented, examining their characteristics for both text representation and text classification. The focus of this survey is on computational requirements and settings rather than on linguistic or literary issues. We also discuss evaluation methodologies and criteria for authorship attribution studies and list open questions that will attract future work in this area. ER - TY - JOUR AU - Vinciarelli, Alessandro AU - Pantic, Maja AU - Bourlard, Hervé T1 - Social signal processing: Survey of an emerging domain JO - Image and Vision Computing PY - 2009/november VL - 27 IS - 12 SP - 1743 EP - 1759 UR - http://dx.doi.org/10.1016/j.imavis.2008.11.007 DO - 10.1016/j.imavis.2008.11.007 KW - everyaware KW - introduction KW - signal KW - social KW - survey L1 - SN - N1 - CiteULike: Social signal processing: Survey of an emerging domain N1 - AB - The ability to understand and manage social signals of a person we are communicating with is the core of social intelligence. Social intelligence is a facet of human intelligence that has been argued to be indispensable and perhaps the most important for success in life. This paper argues that next-generation computing needs to include the essence of social intelligence – the ability to recognize human social signals and social behaviours like turn taking, politeness, and disagreement – in order to become more effective and more efficient. Although each one of us understands the importance of social signals in everyday life situations, and in spite of recent advances in machine analysis of relevant behavioural cues like blinks, smiles, crossed arms, laughter, and similar, design and development of automated systems for social signal processing (SSP) are rather difficult. This paper surveys the past efforts in solving these problems by a computer, it summarizes the relevant findings in social psychology, and it proposes a set of recommendations for enabling the development of the next generation of socially aware computing. ER - TY - JOUR AU - Cimiano, Philipp AU - V"olker, Johanna AU - Studer, Rudi T1 - Ontologies on Demand? -A Description of the State-of-the-Art, Applications, Challenges and Trends for Ontology Learning from Text Information JO - Information, Wissenschaft und Praxis PY - 2006/ VL - 57 IS - 6-7 SP - 315 EP - 320 UR - http://www.aifb.uni-karlsruhe.de/Publikationen/showPublikation?publ_id=1282 DO - KW - learning KW - ol KW - ontology KW - survey L1 - SN - N1 - Ontologies on Demand? - A Description of the State-of-the-Art, Applications, Challenges and Trends for Ontology Learning from Text N1 - AB - ER - TY - JOUR AU - Berkhin, Pavel T1 - A survey on pagerank computing JO - Internet Mathematics PY - 2005/ VL - 2 IS - SP - 73 EP - 120 UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.102.2294 DO - KW - data KW - mining KW - pagerank KW - survey L1 - SN - N1 - A survey on pagerank computing N1 - AB - Abstract. This survey reviews the research related to PageRank computing. Components of a PageRank vector serve as authority weights for web pages independent of their textual content, solely based on the hyperlink structure of the web. PageRank is typically used as a web search ranking component. This defines the importance of the model and the data structures that underly PageRank processing. Computing even a single PageRank is a difficult computational task. Computing many PageRanks is a much more complex challenge. Recently, significant effort has been invested in building sets of personalized PageRank vectors. PageRank is also used in many diverse applications other than ranking. We are interested in the theoretical foundations of the PageRank formulation, in the acceleration of PageRank computing, in the effects of particular aspects of web graph structure on the optimal organization of computations, and in PageRank stability. We also review alternative models that lead to authority indices similar to PageRank and the role of such indices in applications other than web search. We also discuss linkbased search personalization and outline some aspects of PageRank infrastructure from associated measures of convergence to link preprocessing. 1. ER - TY - CONF AU - Brank, Janez AU - Grobelnik, Marko AU - Mladenić, Dunja A2 - T1 - A Survey of Ontology Evaluation Techniques T2 - Proc. of 8th Int. multi-conf. Information Society PB - C1 - PY - 2005/ CY - VL - IS - SP - 166 EP - 169 UR - DO - KW - evaluation KW - ol KW - ontology KW - survey L1 - SN - N1 - A nice survey of ontology evaluation methods, easy to read. N1 - AB - ER - TY - RPRT AU - Gómez-Pérez, Asuncion AU - Manzano-Macho, David A2 - T1 - A survey of ontology learning methods and techniques PB - OntoWeb Consortium AD - PY - 2003/ VL - IS - 1.5 SP - EP - UR - http://www.deri.at/fileadmin/documents/deliverables/Ontoweb/D1.5.pdf DO - KW - learning KW - ol KW - ontology KW - survey L1 - N1 - N1 - Deliverable N1 - AB - ER -