The first international workshop on entity-oriented search (EOS)

The First International Workshop on Entity-Oriented Search (EOS) workshop was held on July 28, 2011 in Beijing, China, in conjunction with the 34th Annual International ACM SIGIR Conference (SIGIR 2011). The objective for the workshop was to bring together academic researchers and industry practitioners working on entity-oriented search to discuss tasks and challenges, and to uncover the next frontiers for academic research on the topic. The workshop program accommodated two invited talks, eleven refereed papers divided into three technical paper sessions, and a group discussion.

[1]  Jian Xu,et al.  High Performance Clustering for Web Person Name Disambiguation Using Topic Capturing , 2011 .

[2]  WenJi-Rong,et al.  The first international workshop on entity-oriented search (EOS) , 2012 .

[3]  Krisztian Balog,et al.  The Sindice-2011 Dataset for Entity-Oriented Search in the Web of Data , 2011 .

[4]  Craig MacDonald,et al.  Exploiting query reformulations for web search result diversification , 2010, WWW '10.

[5]  Richard Tzong-Han Tsai,et al.  Extracting Dish Names from Chinese Blog Reviews Using Suffix Arrays and a Multi-Modal CRF Model , 2011 .

[6]  Heng Ji,et al.  An Evaluation Framework for Aggregated Temporal Information Extraction , 2011 .

[7]  C. Lee Giles,et al.  Learning to Rank Homepages For Researcher-Name Queries , 2011 .

[8]  Olga Vechtomova,et al.  Unsupervised related entity finding , 2011 .

[9]  Sreenivas Gollapudi,et al.  Diversifying search results , 2009, WSDM '09.

[10]  Peter Mika,et al.  Entity Search Evaluation over Structured Web Data , 2011 .

[11]  Raymond Y. K. Lau,et al.  Semi-supervised Statistical Inference for Business Entities Extraction and Business Relations Discovery , 2011 .

[12]  Ralph Grishman,et al.  Cross-Domain Bootstrapping for Named Entity Recognition , 2011 .

[13]  Qi Li Finding Support Documents with a Logistic Regression Approach , 2011 .

[14]  Kevin Dela Rosa,et al.  LADS : Rapid Development of a Learning-To-Rank Based Related Entity Finding System using Open Advancement , 2011 .