A system for finding biological entities that satisfy certain conditions from texts
Proceedings of the 17th ACM conference on Information and knowledge management
Specialized Review Selection for Feature Rating Estimation
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Kernel latent semantic analysis using an information retrieval based kernel
Proceedings of the 18th ACM conference on Information and knowledge management
A negative category based approach for Wikipedia document classification
International Journal of Knowledge Engineering and Data Mining
DOCODE-lite: a meta-search engine for document similarity retrieval
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part II
A similarity matrix-based hybrid algorithm for the contact map overlaps problem
Computers in Biology and Medicine
Batch text similarity search with MapReduce
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
Mining cell cycle literature using support vector machines
SETN'12 Proceedings of the 7th Hellenic conference on Artificial Intelligence: theories and applications
Using contextual spaces for image re-ranking and rank aggregation
Multimedia Tools and Applications
Multimodal retrieval with relevance feedback based on genetic programming
Multimedia Tools and Applications
| Hi-index | 3.84 |
Motivation: The most widely used literature search techniques, such as those offered by NCBI's PubMed system, require significant effort on the part of the searcher, and inexperienced searchers do not use these systems as effectively as experienced users. Improved literature search engines can save researchers time and effort by making it easier to locate the most important and relevant literature. Results: We have created and optimized a new, hybrid search system for Medline that takes natural text as input and then delivers results with high precision and recall. The combination of a fast, low-sensitivity weighted keyword-based first pass algorithm to cast a wide net to gather an initial set of literature, followed by a unique sentence-alignment based similarity algorithm to rank order those results was developed that is sensitive, fast and easy to use. Several text similarity search algorithms, both standard and novel, were implemented and tested in order to determine which obtained the best results in information retrieval exercises. Availability: Literature searching algorithms are implemented in a system called eTBLAST, freely accessible over the web at http://invention.swmed.edu. A variety of other derivative systems and visualization tools provides the user with an enhanced experience and additional capabilities. Contact: Harold.Garner@UTSouthwestern.edu