DocumentCode
3425150
Title
Learning contextual behavior of text data
Author
Bayrak, Coskun ; Joshi, Hemant
Author_Institution
Dept. of Comput. Sci., Arkansas Univ., Little Rock, AR, USA
fYear
2005
fDate
15-17 Dec. 2005
Abstract
Understanding contextual behavior is very important in order to develop a context-aware retrieval system. This paper discusses the philosophy behind the development of the "evolutionary behavior of textual semantics" (EBOTS) system. The EBOTS system is retrieval oriented knowledge representation and management system. This paper proposes a formal model of correlation that can be combined with traditional local and global weighing schemes. Intuitive contextual behavior is studied as a part of proposed research work. Context retrieval based on semantic knowledge allows abstract queries to be defined, instead of exact word-based queries. The results of the context retrieval for a classic3 and time dataset using the EBOTS system have been discussed in this paper. The paper makes a contribution to the semantic knowledge representation and retrieval algorithms.
Keywords
formal specification; knowledge representation; learning (artificial intelligence); programming language semantics; query formulation; text analysis; abstract query; context aware retrieval system; evolutionary behavior; formal model; global weighing scheme; intuitive contextual behavior; management system; retrieval algorithm; semantic knowledge representation; text data; textual semantics; word based query; Computer science; Context modeling; Costs; Information retrieval; Knowledge management; Knowledge representation; Natural language processing; Natural languages; Text analysis; Web sites;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Applications, 2005. Proceedings. Fourth International Conference on
Print_ISBN
0-7695-2495-8
Type
conf
DOI
10.1109/ICMLA.2005.46
Filename
1607466
Link To Document