Constructing query-specific knowledge bases

Abstract Large general purpose knowledge bases (KB) support a variety of complex tasks because of their structured relationships. However, these KBs lack coverage for specialized topics or use cases. In these scenarios, users often use keyword search over large unstructured collections, such as the web. Instead, we propose constructing a 'knowledge sketch' that leverages existing KB data elements and relevant text documents to construct query-specific KB data. A knowledge sketch is a distribution over entities, documents, and relationships between entities, all for a specific information need. In our experiments we construct knowledge sketches for queries from the TREC 2004 Robust track, which emphasizes complex queries which perform poorly with existing text retrieval approaches.

[1]  W. Bruce Croft,et al.  Learning concept importance using a weighted dependence model , 2010, WSDM '10.

[2]  Andrew McCallum,et al.  Query-Aware MCMC , 2011, NIPS.

[3]  Feng Niu,et al.  Building an Entity-Centric Stream Filtering Test Collection for TREC 2012 , 2012, TREC.

[4]  Evgeniy Gabrilovich,et al.  Concept-Based Feature Generation and Selection for Information Retrieval , 2008, AAAI.

[5]  Gerhard Weikum,et al.  WWW 2007 / Track: Semantic Web Session: Ontologies ABSTRACT YAGO: A Core of Semantic Knowledge , 2022 .

[6]  Peter Mika,et al.  Ad-hoc object retrieval in the web of data , 2010, WWW '10.

[7]  Jennifer Chu-Carroll,et al.  Statistical source expansion for question answering , 2011, CIKM '11.

[8]  Ellen M. Voorhees,et al.  Overview of the TREC 2004 Robust Retrieval Track , 2004 .

[9]  W. Bruce Croft,et al.  A Markov random field model for term dependencies , 2005, SIGIR '05.

[10]  Heng Ji,et al.  Overview of the TAC 2010 Knowledge Base Population Track , 2010 .

[11]  Praveen Paritosh,et al.  Freebase: a collaboratively created graph database for structuring human knowledge , 2008, SIGMOD Conference.

[12]  Ellen M. Voorhees,et al.  Evaluating Stream Filtering for Entity Profile Updates in TREC 2012, 2013, and 2014 , 2014, TREC.

[13]  Jaime G. Carbonell,et al.  Retrieval and feedback models for blog feed search , 2008, SIGIR '08.

[14]  Yang Xu,et al.  Query dependent pseudo-relevance feedback based on wikipedia , 2009, SIGIR.

[15]  Laura Dietz,et al.  A neighborhood relevance model for entity linking , 2013, OAIR.

[16]  W. Bruce Croft,et al.  Effective query formulation with multiple information sources , 2012, WSDM '12.

[17]  Evgeniy Gabrilovich,et al.  Computing Semantic Relatedness Using Wikipedia-based Explicit Semantic Analysis , 2007, IJCAI.