Education, training and marketing for online information retrieval systems

Online Review ◽  
1979 ◽  
Vol 3 (2) ◽  
pp. 205-212
Author(s):  
Lucy A. Tedd
Keyword(s):  
Information Retrieval ◽  
Online Information ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Education Training

Online Information Retrieval Systems Trending From Evolutionary to Revolutionary Approach

2019 ◽  
pp. 303-317
Author(s):  
Zahid Ashraf Wani ◽  
Huma Shafiq
Keyword(s):  
Information Retrieval ◽  
Information Needs ◽  
Online Information ◽  
Retrieval Systems ◽  
Diverse Species ◽  
Different Types ◽  
The Future ◽  
Information Retrieval Systems ◽  
Information Professionals ◽  
The Web

Nowadays, we all rely on cyberspace for our information needs. We make use of different types of search tools. Some of them have specialization in a specific format or two, while few can crawl a good portion of the web irrespective of formats. Therefore, it is very imperative for information professionals to have thorough understandings of these tools. As such, the chapter is an endeavor to delve deep and highlight various trends in online information retrieval from primitive to modern ones. The chapter also made an effort to envisage the future requirements and expectation keeping in view the ever-increasing dependence on diverse species of information retrieval tools.

scholarly journals Conflation Methods in Stemming Algorithm

2019 ◽  
Vol 8 (11S) ◽  
pp. 1176-1180
Keyword(s):  
Information Retrieval ◽  
Source Code ◽  
Online Information ◽  
Source Information ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
The Given ◽  
Investigation Process ◽  
Examination Process ◽  
The Web

We began the domain examination process by social occasion source information. We gathered distributed papers in the conflation algorithms branch of knowledge as domain archives and the source code of conflation algorithms for system engineering examination. In the wake of building skill about the conflation algorithms domain, we rounded out system portrayal surveys for every last one of these algorithms. Imperative segments of our domain investigation process are in the accompanying subsections. With the gigantic measure of information accessible on the web, it is extremely fundamental to recover precise information for some client inquiry. There are heaps of methodologies used to expand the adequacy of online information retrieval. The conventional methodology used to recover information for some client question is to search the reports present in the corpus word by word for the given inquiry. This methodology is extremely tedious and it might miss a portion of the related records of equivalent significance. Therefore to stay away from these circumstances, Stemming has been broadly utilized in different Information Retrieval Systems to build the retrieval exactness

An Overview of Online Information Retrieval Systems

2021 ◽  
pp. 1-12
Author(s):  
Christine L. Borgman ◽  
Dineh Moghdam ◽  
Patti K. Corbett
Keyword(s):  
Information Retrieval ◽  
Online Information ◽  
Retrieval Systems ◽  
Information Retrieval Systems

scholarly journals The use of a heuristic process to evaluate an online information retrieval interface.

2013 ◽  
Vol 30 (95) ◽  
pp. 3-9 ◽  
Author(s):  
S M Zabed Ahmed ◽  
Cliff McKnight ◽  
Charles Oppenhein
Keyword(s):  
Information Retrieval ◽  
Human Factors ◽  
User Interfaces ◽  
Web Of Science ◽  
Online Information ◽  
Heuristic Evaluation ◽  
Online Help ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
The Web

This paper presents the results of a heuristic evaluation with the Web of Science interface. Three human factors experts carried out their independent evaluation. The findings were then analysed and combined to discuss them with expert members to reach a consensus on usability issues identified. The heuristic evaluation helped to identify a number of both positive and negative aspects in the Web of Science interface. The key strength of the then current interface was its consistency in terms of conventions used, screen layouts, minimum use of colours, and use of graphics and icons.The main weakness lay in its functionality, i.e., searching, navigation, online help, etc. The results show the effectiveness of a heuristlc approach to evaluating user interfaces to online information retrieval systems.

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