Report on the fifth workshop on exploiting semantic annotations in information retrieval (ESAIR'12)

Author:

Kamps Jaap1,Karlgren Jussi2,Mika Peter3,Murdock Vanessa4

Affiliation:

1. University of Amsterdam, The Netherlands

2. Gavagai, Sweden

3. Yahoo! Research Barcelona, Spain

4. Microsoft Bing, USA

Abstract

There is an increasing amount of structure on the web as a result of modern web languages, user tagging and annotation, emerging robust NLP tools, and an ever growing volume of linked data. These meaningful, semantic, annotations hold the promise to significantly enhance information access, by enhancing the depth of analysis of today's systems. Currently, we have only started exploring the possibilities and only begin to understand how these valuable semantic cues can be put to fruitful use. To complicate matters, standard text search excels at shallow information needs expressed by short keyword queries, and here semantic annotation contributes very little, if anything. The main questions for the workshop are how to leverage the rich context currently available, especially in a mobile search scenario, giving powerful new handles to exploit semantic annotations. And how can we fruitfully combine information retrieval and knowledge intensive approaches, and for the first time work actively toward a unified view on exploiting semantic annotations. There was a strong feeling that we made substantial progress. Specifically, each of the breakout groups contributed to our understanding of the way forward. First, there is a need for further integration of symbolic and statistical methods with each adopting parts of the other's strengths, by focusing on types of annotations that are informed by and meaningful for the task at hand, and relying on automatic information extraction and annotation based on web scale observations. Second, the discussion contributed to the creation of a concrete shared corpus with state of the art semantic annotation--in particular a web crawl annotated with Freebase concepts--that will benefit research in this area for years to come.

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Management Information Systems

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. From XML Retrieval to Semantic Search and Beyond;Information Retrieval Evaluation in a Changing World;2019

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