The hybrid application of an inductive learning method and a neural network for intelligent information retrieval

1995 ◽  
Vol 31 (6) ◽  
pp. 789-813 ◽  
Author(s):  
Edwin M. Cortez ◽  
Sang C. Park ◽  
Seonghee Kim
Keyword(s):  
Neural Network ◽  
Information Retrieval ◽  
Inductive Learning ◽  
Learning Method ◽  
Intelligent Information Retrieval ◽  
Intelligent Information

scholarly journals RESEARCH OF APPROACHES TO THE RECOGNITION OF SEMANTIC IMAGES OF SCIENTIFIC PUBLICATIONS BASED ON NEURAL NETWORKS

2021 ◽  
Vol 2 ◽  
pp. 38-43
Author(s):  
Iuliia Bruttan ◽  
Igor Antonov ◽  
Dmitry Andreev ◽  
Victor Nikolaev ◽  
Tatyana Klets
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Information Retrieval ◽  
Scientific Publication ◽  
Scientific Publications ◽  
Network Training ◽  
Retrieval Systems ◽  
Intelligent Information Retrieval ◽  
Information Retrieval Systems ◽  
Intelligent Information

The paper is devoted to the problems of orientation and navigation in the world of verbal presentation of scientific knowledge. The solution of these problems is currently hampered by the lack of intelligent information retrieval systems that allow comparing descriptions of various scientific works at the level of coincidence of semantic situations, rather than keywords. The article discusses methods for the formation and recognition of semantic images of scientific publications belonging to specific subject areas. The method for constructing a semantic image of a scientific text developed by Iuliia Bruttan allows to form an image of the text of a scientific publication, which can be used as input data for a neural network. Training of this neural network will automate the processes of pattern recognition and classification of scientific publications according to specified criteria. The approaches to the recognition of semantic images of scientific publications based on neural networks considered in the paper can be used to organize the semantic search for scientific publications, as well as in the design of intelligent information retrieval systems.

scholarly journals Intelligent Information Retrieval Using Hybrid of Fuzzy Set and Trust

2017 ◽  
Vol 10 (2) ◽  
pp. 311-325
Author(s):  
Suruchi Chawla
Keyword(s):  
Information Retrieval ◽  
Fuzzy Set ◽  
Query Expansion ◽  
Information Need ◽  
Data Set ◽  
Search Results ◽  
Intelligent Information Retrieval ◽  
Main Challenge ◽  
Fuzzy Query ◽  
Intelligent Information

The main challenge for effective web Information Retrieval(IR) is to infer the information need from user’s query and retrieve relevant documents. The precision of search results is low due to vague and imprecise user queries and hence could not retrieve sufficient relevant documents. Fuzzy set based query expansion deals with imprecise and vague queries for inferring user’s information need. Trust based web page recommendations retrieve search results according to the user’s information need. In this paper an algorithm is designed for Intelligent Information Retrieval using hybrid of Fuzzy set and Trust in web query session mining to perform Fuzzy query expansion for inferring user’s information need and trust is used for recommendation of web pages according to the user’s information need. Experiment was performed on the data set collected in domains Academics, Entertainment and Sports and search results confirm the improvement of precision.

Sign in / Sign up

Export Citation Format

Share Document