Analysis of a very large web search engine query log
ACM SIGIR Forum
Searching the Web: the public and their queries
Journal of the American Society for Information Science and Technology
Term proximity scoring for ad-hoc retrieval on very large text collections
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
An Adaptation of the Vector-Space Model for Ontology-Based Information Retrieval
IEEE Transactions on Knowledge and Data Engineering
An exploration of proximity measures in information retrieval
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Proximity-based document representation for named entity retrieval
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
VN-KIM IE: automatic extraction of Vietnamese named-entities on the web
New Generation Computing
Exploring Combinations of Ontological Features and Keywords for Text Retrieval
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Term proximity scoring for keyword-based retrieval systems
ECIR'03 Proceedings of the 25th European conference on IR research
LRD: latent relation discovery for vector space expansion and information retrieval
WAIM '06 Proceedings of the 7th international conference on Advances in Web-Age Information Management
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This paper presents our developed general open source for ontology-based information retrieval to answer queries that involve named entities with their ontological features, namely, aliases, classes, and identifiers. We propose a novel approach for semantic search engines that exploit the ontology features of named entities in proximity search and develop an algorithm for computing dynamic distances between named entities and keywords in queries and documents. In particular, it deals with phrase and proximity queries for which the token-based lengths and positions of the queried named entities in a document may vary. The result provides a platform and library for implementing semantic search engines.