Search results for Fabio Crestani
211 results found. Showing ( 1 -» 10 ).
1
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This book constitutes the proceedings of the 34th European Conference on IR Research, ECIR 2012, held in Barcelona, Spain, in April 2012. The 37 full papers, 28 poster papers and 7 demonstrations presented in this volume were carefully reviewed and selected from 167 submissions. The contributions are organized in sections named: query representation; blogs and online-community search; semi-structured retrieval; evaluation; applications; retrieval models; image and video retrieval; text and content classification, categorisation, clustering; systems efficiency; industry track; and posters.
Ricardo Baeza-Yates |
Arjen P. De Vries |
Hugo Zaragoza |
B. Barla Cambazoglu |
Vanessa Murdock |
Ronny Lempel |
Fabrizio Silvestri
Database management
2
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The two-volume set LNCS 7066 and LNCS 7067 constitutes the proceedings of the Second International Visual Informatics Conference, IVIC 2011, held in Selangor, Malaysia, during November 9-11, 2011.The 71 revised papers presented were carefully reviewed and selected for inclusion in these proceedings. They are organized in topical sections named computer vision and simulation; virtual image processing and engineering; visual computing; and visualisation and social computing. In addition the first volume contains two keynote speeches in full paper length, and one keynote abstract.
Halimah Badioze Zaman |
Peter Robinson |
Maria Petrou |
Patrick Olivier |
Timothy K. Shih |
Sergio Velastin
Unknown
3
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This book constitutes the refereed proceedings of the 13th International Conference on Asia-Pacific Digital Libraries, ICADL 2011, held in Beijing, China, in October 2011. The 33 revised full papers, 8 short papers and 9 poster papers presented were carefully reviewed and selected from 136 submissions. The topics covered are digital archives and preservation; information mining and extraction; medata, catalogue; distributed repositories and cloud computing; social network and personalized service; mobile services and electronic publishing; multimedia digital libraries; information retrieval; and tools and systems for digital library.
Chunxiao Xing |
Fabio Crestani |
Andreas Rauber
Unknown
4
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This book constitutes the refereed proceedings of the International Conference on Theory and Practice of Digital Libraries, TPDL 2011 - formerly known as ECDL (European Conference on Research and Advanced Technology for Digital Libraries) - held in Berlin, Germany, in September 2011. The 27 full papers, 13 short papers, 9 posters and 9 demos presented in this volume were carefully reviewed and selected from 162 initial submissions. In addition the book contains the abstract of 2 keynote speeches and an appendix stating information on the doctoral consortium, as well as the panel, which were held at the conference. The papers are grouped in topical sections on networked information, semantics and interoperability, systems and architectures, text and multimedia retrieval, collaborative information spaces, DL applications and legal aspects, user interaction and information visualization, user studies, archives and repositories, europeana, and preservation.
Stefan Gradmann |
Francesca Borri |
Carlo Meghini |
Heiko Schuldt
Unknown
5
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This book constitutes the refereed proceedings of the Third International Conference on the Theory of Information Retrieval, ICTIR 2011, held in Bertinoro, Italy, in September 2011. The 25 revised full papers and 13 short papers presented together with the abstracts of two invited talks were carefully reviewed and selected from 65 submissions. The papers cover topics ranging from query expansion, co-occurence analysis, user and interactive modelling, system performance prediction and comparison, and probabilistic approaches for ranking and modelling IR to topics related to interdisciplinary approaches or applications. They are organized into the following topical sections: predicting query performance; latent semantic analysis and word co-occurrence analysis; query expansion and re-ranking; comparison of information retrieval systems and approximate search; probability ranking principle and alternatives; interdisciplinary approaches; user and relevance; result diversification and query disambiguation; and logical operators and descriptive approaches.
Giambattista Amati |
Fabio Crestani
Unknown
6
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This publication reflects the myriad theories that have developed over the past century to explain how we acquire, organize and deploy knowledge and skills. Providing up-to-date, wide-ranging and authoritative coverage, this is the first reference of its kind.
Norbert M. Seel
Unknown
7
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The inflammasome was first described in 2002 as a molecular complex activating proinflammatory caspases and therefore regulating the maturation and biological activities of cytokines such as IL-1? and IL-18. This finding was substantiated by the identification of several mutations in the cias1 gene, encoding the human NLRP3 protein, responsible for several autoinflammatory disorders such as the Muckle Wells syndrome. Since, the interest for this complex has constantly increased and several inflammasome complexes with different specificities have been described. These inflammasomes sense a wide variety of pathogens and danger signals and are key players in the inflammatory response. With the contributions of leading international experts in the field, this book provides an extensive overview of the current knowledge of inflammasome biology and their role in health and disease.
Isabelle Couillin |
Virginie Pétrilli |
Fabio Martinon
Medical
8
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Information retrieval is the science concerned with the effective and efficient retrieval of documents starting from their semantic content. It is employed to fulfill some information need from a large number of digital documents. Given the ever-growing amount of documents available and the heterogeneous data structures used for storage, information retrieval has recently faced and tackled novel applications. In this book, Melucci and Baeza-Yates present a wide-spectrum illustration of recent research results in advanced areas related to information retrieval. Readers will find chapters on e.g. aggregated search, digital advertising, digital libraries, discovery of spam and opinions, information retrieval in context, multimedia resource discovery, quantum mechanics applied to information retrieval, scalability challenges in web search engines, and interactive information retrieval evaluation. All chapters are written by well-known researchers, are completely self-contained and comprehensive, and are complemented by an integrated bibliography and subject index. With this selection, the editors provide the most up-to-date survey of topics usually not addressed in depth in traditional (text)books on information retrieval. The presentation is intended for a wide audience of people interested in information retrieval: undergraduate and graduate students, post-doctoral researchers, lecturers, and industrial researchers.
Massimo Melucci |
Ricardo Baeza-Yates
Computers
9
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The LNCS series reports state-of-the-art results in computer science research, development, and education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R & D community, with numerous individuals, as well as with prestigious organizations and societies, LNCS has grown into the most comprehensive computer science research forum available.
Allan Hanbury |
Andreas Rauber |
Arjen Vries
Unknown
10
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This book constitutes the refereed proceedings of the 33rd annual European Conference on Information Retrieval Research, ECIR 2011, held in Dublin, Ireland, in April 2010. The 45 revised full papers presented together with 24 poster papers, 17 short papers, and 6 tool demonstrations were carefully reviewed and selected from 223 full research paper submissions and 64 poster/demo submissions. The papers are organized in topical sections on text categorization, recommender systems, Web IR, IR evaluation, IR for Social Networks, cross-language IR, IR theory, multimedia IR, IR applications, interactive IR, and question answering /NLP.
Paul Clough |
Colum Foley |
Cathal Gurrin |
Gareth J. F. Jones |
Wessel Kraaij |
Hyowon Lee
Unknown
11
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Learning to rank refers to machine learning techniques for training the model in a ranking task. Learning to rank is useful for many applications in information retrieval, natural language processing, and data mining. Intensive studies have been conducted on the problem recently and significant progress has been made. This lecture gives an introduction to the area including the fundamental problems, existing approaches, theories, applications, and future work.The author begins by showing that various ranking problems in information retrieval and natural language processing can be formalized as two basic ranking tasks, namely ranking creation (or simply ranking) and ranking aggregation. In ranking creation, given a request, one wants to generate a ranking list of offerings based on the features derived from the request and the offerings. In ranking aggregation, given a request, as well as a number of ranking lists of offerings, one wants to generate a new ranking list of the offerings.Ranking creation (or ranking) is the major problem in learning to rank. It is usually formalized as a supervised learning task. The author gives detailed explanations on learning for ranking creation and ranking aggregation, including training and testing, evaluation, feature creation, and major approaches. Many methods have been proposed for ranking creation. The methods can be categorized as the pointwise, pairwise, and listwise approaches according to the loss functions they employ. They can also be categorized according to the techniques they employ, such as the SVM based, Boosting SVM, Neural Network based approaches.The author also introduces some popular learning to rank methods in details. These include PRank, OC SVM, Ranking SVM, IR SVM, GBRank, RankNet, LambdaRank, ListNet & ListMLE, AdaRank, SVM MAP, SoftRank, Borda Count, Markov Chain, and CRanking.The author explains several example applications of learning to rank including web search, collaborative filtering, definition search, keyphrase extraction, query dependent summarization, and re-ranking in machine translation.A formulation of learning for ranking creation is given in the statistical learning framework. Ongoing and future research directions for learning to rank are also discussed.Table of Contents: Introduction / Learning for Ranking Creation / Learning for Ranking Aggregation / Methods of Learning to Rank / Applications of Learning to Rank / Theory of Learning to Rank / Ongoing and Future Work
Hang Li |
Graeme Hirst
Computers
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