Aspects of Intelligence in an "SP" Database System

2009 ◽  
pp. 725-754
Author(s):  
J. Gerard Wolff
Keyword(s):  
Pattern Recognition ◽  
Information Retrieval ◽  
Natural Language ◽  
Unsupervised Learning ◽  
Probabilistic Reasoning ◽  
Database System ◽  
Theory Of Computing ◽  
New Knowledge ◽  
Database Models

This chapter describes some of the kinds of “intelligence” that may be exhibited by an intelligent database system based on the SP theory of computing and cognition. The chapter complements an earlier paper on the SP theory as the basis for an intelligent database system (Wolff, forthcoming b) but it does not depend on a reading of that earlier paper. The chapter introduces the SP theory and its main attractions as the basis for an intelligent database system: that it uses a simple but versatile format for diverse kinds of knowledge, that it integrates and simplifies a range of AI functions, and that it supports established database models when that is required. Then with examples and discussion, the chapter illustrates aspects of “intelligence” in the system: pattern recognition and information retrieval, several forms of probabilistic reasoning, the analysis and production of natural language, and the unsupervised learning of new knowledge.

Aspects of Intelligence in an "SP" Database System

2011 ◽  
pp. 197-237
Author(s):  
J. Gerard Wolff
Keyword(s):  
Pattern Recognition ◽  
Information Retrieval ◽  
Natural Language ◽  
Unsupervised Learning ◽  
Probabilistic Reasoning ◽  
Database System ◽  
Theory Of Computing ◽  
New Knowledge ◽  
Database Models

This chapter describes some of the kinds of “intelligence” that may be exhibited by an intelligent database system based on the SP theory of computing and cognition. The chapter complements an earlier paper on the SP theory as the basis for an intelligent database system (Wolff, forthcoming b) but it does not depend on a reading of that earlier paper. The chapter introduces the SP theory and its main attractions as the basis for an intelligent database system: that it uses a simple but versatile format for diverse kinds of knowledge, that it integrates and simplifies a range of AI functions, and that it supports established database models when that is required. Then with examples and discussion, the chapter illustrates aspects of “intelligence” in the system: pattern recognition and information retrieval, several forms of probabilistic reasoning, the analysis and production of natural language, and the unsupervised learning of new knowledge.

scholarly journals Ordering of Huge Biometric Information in Database System

2021 ◽  
Vol 2 (2) ◽  
pp. 1-19
Author(s):  
Varisha Alam ◽  
Keyword(s):  
Information Retrieval ◽  
Database System ◽  
Error Rates ◽  
Behavioral Characteristics ◽  
Access Management ◽  
Retrieval Time ◽  
Biological Features ◽  
Reduced Rate ◽  
Improved Accuracy ◽  
Biometric Information

The word biometrics is derived from the Greek words 'bios' and 'metric' which means living and calculation appropriately. Biometrics is the electronic identification of individuals based on their physiological and biological features. Biometric attributes are data take out from biometric test which can be used for contrast with a biometric testimonial. Biometrics composed methods for incomparable concede humans based upon one or more inherent material or behavioral characteristics. In Computer Science, bio-metrics is employed as a kind of recognition access management and access command. Biometrics has quickly seemed like an auspicious technology for attestation and has already found a place in the most sophisticated security areas. A systematic clustering technique has been there for partitioning huge biometric databases throughout recognition. As we tend to are still obtaining the higher bin-miss rate, so this work is predicated on conceiving an ordering strategy for recognition of huge biometric database and with larger precision. This technique is based on the modified B+ tree that decreases the disk accesses. It reduced the information retrieval time and feasible error rates. The ordering technique is employed to proclaims a person’s identity with a reduced rate of differentiation instead of searching the whole database. The response time degenerates, further-more because the accuracy of the system deteriorates as the size of the database increases. Hence, for vast applications, the requirement to reduce the database to a little fragment seems to attain higher speeds and improved accuracy.

scholarly journals Architecture of a concept-based information retrieval system for educational resources

2016 ◽  
Vol 129 ◽  
pp. 72-91 ◽  
Author(s):  
Roberto Pérez-Rodríguez ◽  
Luis Anido-Rifón ◽  
Miguel Gómez-Carballa ◽  
Marcos Mouriño-García
Keyword(s):  
Information Retrieval ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Educational Resources

scholarly journals The Information Retrieval Competencies of Students Faced with Remote and Blended Teaching

2021 ◽  
Vol 24 (3) ◽  
pp. 446-464
Author(s):  
Alla Aleksandrovna Vitukhnovskaya
Keyword(s):  
Information Retrieval ◽  
Information Systems ◽  
Remote Access ◽  
Educational Resources ◽  
Student Survey ◽  
Electronic Information ◽  
Remote Education ◽  
Blended Teaching

The article describes the problems and features of information retrieval activity of students amid the extreme transition of universities to remote education. The results of a student survey are described, allowing to gain some initial insights into the information retrieval competencies of students in a new reality, when the only opportunity for them is remote access to electronic information systems and electronic educational resources. The competencies necessary for effective information retrieval in a remote and blended teaching have been listed and characterized.

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