1983 ◽  
Vol 6 (5) ◽  
pp. 165-172 ◽  
Author(s):  
F.N. Teskey

In this paper the existing functions of, and a number of future requirements for, information retrieval systems are dis cussed. Two basic requirements for free text information retri eval systems have been identified; one for a more general information modelling language and the other for a simple user interface for complex ad-hoc queries. The paper describes some existing and proposed hardware and software methods for implementing free text information retrieval systems. Emphasis is placed on methods of improving the functionality of the system rather than on methods of increasing the performance. It is suggested that considerable improvements can be achieved by a more imaginative use of existing hardware, though it is realised that special purpose architectures will play an increas ingly important role in information systems. The paper con cludes with a design for a new information retrieval system based on the use of the Binary Relationship Model for infor mation storage and retrieval, and an interactive graphical dis play for the user interface.


Author(s):  
Antonio Picariello

Information retrieval can take great advantages and improvements considering users’ feedbacks. Therefore, the user dimension is a relevant component that must be taken into account while planning and implementing real information retrieval systems. In this chapter, we first describe several concepts related to relevance feedback methods, and then propose a novel information retrieval technique which uses the relevance feedback concepts in order to improve accuracy in an ontology-based system. In particular, we combine the Semantic information from a general knowledge base with statistical information using relevance feedback. Several experiments and results are presented using a test set constituted of Web pages.


Author(s):  
Antonio Picariello ◽  
Antonio M. Rinaldi

The user dimension is a crucial component in the information retrieval process and for this reason it must be taken into account in planning and technique implementation in information retrieval systems. In this paper we present a technique based on relevance feedback to improve the accuracy in an ontology based information retrieval system. Our proposed method combines the semantic information in a general knowledge base with statistical information using relevance feedback. Several experiments and results are presented using a test set constituted of Web pages.


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