Ranking For Web Data Search Using On The Fly Data Integration
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Ranking for Web Data Search Using On-The-Fly Data Integration
Author: Herzig, Daniel Markus
language: en
Publisher: KIT Scientific Publishing
Release Date: 2014-01-21
Ranking - the algorithmic decision on how relevant an information artifact is for a given information need and the sorting of artifacts by their concluded relevancy - is an integral part of every search engine. In this book we investigate how structured Web data can be leveraged for ranking with the goal to improve the effectiveness of search. We propose new solutions for ranking using on-the-fly data integration and experimentally analyze and evaluate them against the latest baselines.
The Semantic Web - ISWC 2013
The two-volume set LNCS 8218 and 8219 constitutes the refereed proceedings of the 12th International Semantic Web Conference, ISWC 2013, held in Sydney, Australia, in October 2013. The International Semantic Web Conference is the premier forum for Semantic Web research, where cutting edge scientific results and technological innovations are presented, where problems and solutions are discussed, and where the future of this vision is being developed. It brings together specialists in fields such as artificial intelligence, databases, social networks, distributed computing, Web engineering, information systems, human-computer interaction, natural language processing, and the social sciences. Part 1 (LNCS 8218) contains a total of 45 papers which were presented in the research track. They were carefully reviewed and selected from 210 submissions. Part 2 (LNCS 8219) contains 16 papers from the in-use track which were accepted from 90 submissions. In addition, it presents 10 contributions to the evaluations and experiments track and 5 papers of the doctoral consortium.
Ranking for Web Data Search Using On-The-Fly Data Integration
Ranking - the algorithmic decision on how relevant an information artifact is for a given information need and the sorting of artifacts by their concluded relevancy - is an integral part of every search engine. In this book we investigate how structured Web data can be leveraged for ranking with the goal to improve the effectiveness of search. We propose new solutions for ranking using on-the-fly data integration and experimentally analyze and evaluate them against the latest baselines. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.