Snowball: extracting relations from large plain-text collections
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Extracting Patterns and Relations from the World Wide Web
WebDB '98 Selected papers from the International Workshop on The World Wide Web and Databases
SemTag and seeker: bootstrapping the semantic web via automated semantic annotation
WWW '03 Proceedings of the 12th international conference on World Wide Web
Optimizing scoring functions and indexes for proximity search in type-annotated corpora
Proceedings of the 15th international conference on World Wide Web
Avatar semantic search: a database approach to information retrieval
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Yago: a core of semantic knowledge
Proceedings of the 16th international conference on World Wide Web
Wikify!: linking documents to encyclopedic knowledge
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Proximity-based document representation for named entity retrieval
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Ranking very many typed entities on wikipedia
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
EntityRank: searching entities directly and holistically
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Building structured web community portals: a top-down, compositional, and incremental approach
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
A relational approach to incrementally extracting and querying structure in unstructured data
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Proceedings of the 2008 ACM symposium on Applied computing
Open information extraction from the web
Communications of the ACM - Surviving the data deluge
WebTables: exploring the power of tables on the web
Proceedings of the VLDB Endowment
Learning to link with wikipedia
Proceedings of the 17th ACM conference on Information and knowledge management
A Model for Ranking Entities and Its Application to Wikipedia
LA-WEB '08 Proceedings of the 2008 Latin American Web Conference
NAGA: Searching and Ranking Knowledge
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Collective annotation of Wikipedia entities in web text
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Data-oriented content query system: searching for data into text on the web
Proceedings of the third ACM international conference on Web search and data mining
DBpedia: a nucleus for a web of open data
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
EntityEngine: answering entity-relationship queries using shallow semantics
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Entity-relationship queries over wikipedia
SMUC '10 Proceedings of the 2nd international workshop on Search and mining user-generated contents
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Wikipedia is the largest user-generated knowledge base. We 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. We present a ranking framework for general entity-relationship queries and a position-based Bounded Cumulative Model (BCM) for accurate ranking of query answers. We also explore various weighting schemes for further improving the accuracy of BCM. We test our ideas on a 2008 version of Wikipedia using a collection of 45 queries pooled from INEX entity ranking track and our own crafted queries. Experiments show that the ranking and weighting schemes are both effective, particularly on multipredicate queries.