Paper Info
Title
Relationship Queries on Extended Knowledge Graphs.
Abstract
Entity search over text corpora is not geared for relationship queries where answers are tuples of related entities and where a query often requires joining cues from multiple documents. With large knowledge graphs, structured querying on their relational facts is an alternative, but often suffers from poor recall because of mismatches between user queries and the knowledge graph or because of weakly populated relations. This paper presents the TriniT search engine for querying and ranking on extended knowledge graphs that combine relational facts with textual web contents. Our query language is designed on the paradigm of SPO triple patterns, but is more expressive, supporting textual phrases for each of the SPO arguments. We present a model for automatic query relaxation to compensate for mismatches between the data and a user's query. Query answers -- tuples of entities -- are ranked by a statistical language model. We present experiments with different benchmarks, including complex relationship queries, over a combination of the Yago knowledge graph and the entity-annotated ClueWeb'09 corpus.
Year
DOI
Venue
2016
10.1145/2835776.2835795
WSDM
Keywords
Field
DocType
Relationship Queries, Extended Knowledge Graphs, Query Relaxation
Query optimization,Data mining,Web search query,Query language,Query expansion,Information retrieval,Computer science,Sargable,Web query classification,Spatial query,Boolean conjunctive query
Conference
Citations 
PageRank 
References 
20
0.79
31
Authors
5
Name
Order
Citations
PageRank
Mohamed Yahya118611.65
Denilson Barbosa261043.52
Klaus Berberich3127168.96
Qiuyue Wang4200.79
Gerhard Weikum5127102146.01