Paper Info
Title
Proximity2-aware ranking for textual, temporal, and geographic queries
Abstract
Temporal and geographic information needs are frequent and important but not well served by standard IR systems. Recent approaches address such needs by extracting and normalizing temporal and geographic expressions from documents. They calculate specific scores for the temporal and/ or geographic parts of a query. However, all approaches assume independence between the different query parts. In this paper, we present a new model to rank documents according to combined textual, temporal, and geographic queries. The independence assumption between the query parts is eliminated by calculating proximity scores. Thus, documents are regarded to be more relevant if terms and expressions satisfying the different query parts occur close to each other in a document. As our evaluations based on the NTCIR-GeoTime data show, our proposed model outperforms baseline models that do not use proximity information.
Year
DOI
Venue
2013
10.1145/2505515.2505640
CIKM
Keywords
DocType
Citations 
geographic expression,different query part,new model,geographic information need,geographic query,query part,geographic part,proposed model,independence assumption,Proximity2-aware ranking,baseline model
Conference
2
PageRank 
References 
Authors
0.36
10
2
Name
Order
Citations
PageRank
Jannik Strötgen149238.20
Michael Gertz232527.07