TY - GEN
T1 - Extracting relevant snippets from web documents through language model based text segmentation
AU - Li, Qing
AU - Candan, Kasim
AU - Qi, Yan
PY - 2007
Y1 - 2007
N2 - Extracting a query-oriented snippet (or passage) and highlighting the relevant information in long document can help reduce the result navigation cost of end users. While the traditional approach of highlighting matching keywords helps when the search is keyword oriented, finding appropriate snippets to represent matches to more complex queries requires novel techniques that can help characterize the relevance of various parts of a document to the given query, succinctly. In this paper, we present a languagemodel based method for accurately detecting the most relevant passages of a given document. Unlike previous works in passage retrieval which focus on searching relevance nodes for filtering of preoccupied passages, we focus on query-informed segmentation for snippet extraction. The algorithms presented in this paper are currently being deployed in OASIS, a system to help reduce the navigational load of blind users in accessing Web-based digital libraries.
AB - Extracting a query-oriented snippet (or passage) and highlighting the relevant information in long document can help reduce the result navigation cost of end users. While the traditional approach of highlighting matching keywords helps when the search is keyword oriented, finding appropriate snippets to represent matches to more complex queries requires novel techniques that can help characterize the relevance of various parts of a document to the given query, succinctly. In this paper, we present a languagemodel based method for accurately detecting the most relevant passages of a given document. Unlike previous works in passage retrieval which focus on searching relevance nodes for filtering of preoccupied passages, we focus on query-informed segmentation for snippet extraction. The algorithms presented in this paper are currently being deployed in OASIS, a system to help reduce the navigational load of blind users in accessing Web-based digital libraries.
UR - http://www.scopus.com/inward/record.url?scp=48349103195&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=48349103195&partnerID=8YFLogxK
U2 - 10.1109/WI.2007.56
DO - 10.1109/WI.2007.56
M3 - Conference contribution
AN - SCOPUS:48349103195
SN - 0769530265
SN - 9780769530260
T3 - Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007
SP - 287
EP - 290
BT - Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007
T2 - IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007
Y2 - 2 November 2007 through 5 November 2007
ER -