Difference between revisions of "Entity-Relationship Queries over Wikipedia"
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{{Infobox work | {{Infobox work | ||
| title = Entity-Relationship Queries over Wikipedia | | title = Entity-Relationship Queries over Wikipedia | ||
| − | | date = | + | | date = 2012 |
| authors = [[Xiaonan Li]]<br />[[Chengkai Li]]<br />[[Cong Yu]] | | authors = [[Xiaonan Li]]<br />[[Chengkai Li]]<br />[[Cong Yu]] | ||
| − | | doi = 10.1145/ | + | | doi = 10.1145/2337542.2337555 |
| − | | link = https://dl.acm.org/citation.cfm?doid= | + | | link = https://dl.acm.org/citation.cfm?doid=2337542.2337555 |
}} | }} | ||
| − | '''Entity-Relationship Queries over Wikipedia''' - scientific work related to [[Wikipedia quality]] published in | + | '''Entity-Relationship Queries over Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2012, written by [[Xiaonan Li]], [[Chengkai Li]] and [[Cong Yu]]. |
== Overview == | == Overview == | ||
| − | Wikipedia is the largest user-generated knowledge base. Authors propose a structured query mechanism, entity-relationship query , for searching entities in [[Wikipedia]] corpus by their properties and | + | Wikipedia is the largest user-generated knowledge base. Authors propose a structured query mechanism, entity-relationship query , for searching entities in the [[Wikipedia]] corpus by their properties and interrelationships. An entity-relationship query consists of multiple predicates on desired entities. The semantics of each predicate is specified with keywords. Entity-relationship query searches entities directly over text instead of preextracted structured data stores. This characteristic brings two benefits: (1) Query semantics can be intuitively expressed by keywords; (2) It only requires rudimentary entity annotation, which is simpler than explicitly extracting and reasoning about complex [[semantic information]] before query-time. Authors present a ranking framework for general entity-relationship queries and a position-based Bounded Cumulative Model (BCM) for accurate ranking of query answers. Authors also explore various weighting schemes for further improving the accuracy of BCM. Authors test ideas on a 2008 version of Wikipedia using a collection of 45 queries pooled from INEX entity ranking track and own crafted queries. Experiments show that the ranking and weighting schemes are both effective, particularly on multipredicate queries. |
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Revision as of 22:04, 3 October 2020
Authors | Xiaonan Li Chengkai Li Cong Yu |
|---|---|
Publication date | 2012 |
DOI | 10.1145/2337542.2337555 |
Links | Original |
Entity-Relationship Queries over Wikipedia - scientific work related to Wikipedia quality published in 2012, written by Xiaonan Li, Chengkai Li and Cong Yu.
Overview
Wikipedia is the largest user-generated knowledge base. Authors propose a structured query mechanism, entity-relationship query , for searching entities in the Wikipedia corpus by their properties and interrelationships. An entity-relationship query consists of multiple predicates on desired entities. The semantics of each predicate is specified with keywords. Entity-relationship query searches entities directly over text instead of preextracted structured data stores. This characteristic brings two benefits: (1) Query semantics can be intuitively expressed by keywords; (2) It only requires rudimentary entity annotation, which is simpler than explicitly extracting and reasoning about complex semantic information before query-time. Authors present a ranking framework for general entity-relationship queries and a position-based Bounded Cumulative Model (BCM) for accurate ranking of query answers. Authors also explore various weighting schemes for further improving the accuracy of BCM. Authors test ideas on a 2008 version of Wikipedia using a collection of 45 queries pooled from INEX entity ranking track and own crafted queries. Experiments show that the ranking and weighting schemes are both effective, particularly on multipredicate queries.
