Paper Info
Title
Extraction and evaluation of candidate named entities in search engine queries
Abstract
Named Entity Recognition (NER) has recently been applied to search queries, in order to better understand their semantics. We present a novel method for detecting candidate named entities (NEs) using grammar annotation and query segmentation with the aid of top-n snippets from search engine results, and a web n-gram model to accurately identify NE boundaries. We then evaluate this method automatically using DBpedia as a rich data source of NEs, with the aid of a small representative random sample that is manually annotated. Finally, an analysis of the types of named entities that often occur in a query log is conducted, from which a search query driven named entity taxonomy is presented.
Year
DOI
Venue
2012
10.1007/978-3-642-35063-4_35
WISE
Keywords
Field
DocType
search engine query,entity taxonomy,novel method,query segmentation,grammar annotation,entity recognition,search query,query log,ne boundary,search engine result,rich data source
Web search query,Data mining,Annotation,Search engine,Information retrieval,Computer science,Segmentation,Web query classification,Grammar,Named-entity recognition,Semantics
Conference
Citations 
PageRank 
References 
5
0.51
11
Authors
3
Name
Order
Citations
PageRank
Areej Alasiry1101.25
Mark Levene21272252.84
Alexandra Poulovassilis31222370.61