Social Information Retrieval Systems: Emerging Technologies and Applications for Searching the Web Effectively

2010 ◽  
Vol 61 (12) ◽  
pp. 2587-2588
Author(s):  
Gobinda Chowdhury
Keyword(s):  
Information Retrieval ◽  
Emerging Technologies ◽  
Social Information ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
The Web

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.

User Models for Adaptive Information Retrieval on the Web

2012 ◽  
Vol 3 (3) ◽  
pp. 1-19
Author(s):  
Max Chevalier ◽  
Christine Julien ◽  
Chantal Soulé-Dupuy
Keyword(s):  
Information Retrieval ◽  
Search Engines ◽  
User Profile ◽  
User Model ◽  
User Models ◽  
Search Results ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Adaptive Information Retrieval ◽  
The Web

Searching information can be realized thanks to specific tools called Information Retrieval Systems IRS (also called “search engines”). To provide more accurate results to users, most of such systems offer personalization features. To do this, each system models a user in order to adapt search results that will be displayed. In a multi-application context (e.g., when using several search engines for a unique query), personalization techniques can be considered as limited because the user model (also called profile) is incomplete since it does not exploit actions/queries coming from other search engines. So, sharing user models between several search engines is a challenge in order to provide more efficient personalization techniques. A semantic architecture for user profile interoperability is proposed to reach this goal. This architecture is also important because it can be used in many other contexts to share various resources models, for instance a document model, between applications. It is also ensuring the possibility for every system to keep its own representation of each resource while providing a solution to easily share it.

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

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.

The role of emotional aspects in the information retrieval from the web

2018 ◽  
Vol 42 (4) ◽  
pp. 520-534 ◽  
Author(s):  
Marzieh Yari Zanganeh ◽  
Nadjla Hariri
Keyword(s):  
Information Retrieval ◽  
Individual Characteristics ◽  
Human Interaction ◽  
Emotional Expressions ◽  
Content Type ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Emotional Aspects ◽  
The Web

Purpose The purpose of this paper is to identify the role of emotional aspects in information retrieval of PhD students from the web. Design/methodology/approach From the methodological perspective, the present study is experimental and the type of study is practical. The study population is PhD students of various fields of science. The study sample consists of 50 students as selected by the stratified purposive sampling method. The information aggregation is performed by observing the records of user’s facial expressions, log file by Morae software, as well as pre-search and post-search questionnaire. The data analysis is performed by canonical correlation analysis. Findings The findings showed that there was a significant relationship between emotional expressions and searchers’ individual characteristics. Searchers satisfaction of results, frequency internet search, experience of search, interest in the search task and familiarity with similar searches were correlated with the increased happy emotion. The examination of user’s emotions during searching performance showed that users with happiness emotion dedicated much time in searching and viewing of search solutions. More internet addresses with more queries were used by happy participants; on the other hand, users with anger and disgust emotions had the lowest attempt in search performance to complete search process. Practical implications The results imply that the information retrieval systems in the web should identify emotional expressions in a set of perceiving signs in human interaction with computer, similarity, face emotional states, searching and information retrieval from the web. Originality/value The results explicit in the automatic identification of users’ emotional expressions can enter new dimensions into their moderator and information retrieval systems on the web and can pave the way of design of emotional information retrieval systems for the successful retrieval of users of the network.

Metadata for Social Recommendations

2011 ◽  
pp. 87-108 ◽  
Author(s):  
Riina Vuorikari ◽  
Nikos Manouselis ◽  
Erik Duval
Keyword(s):  
Information Retrieval ◽  
Recommender Systems ◽  
Critical Mass ◽  
Social Information ◽  
Learning Resources ◽  
Evaluation Approach ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Common Framework ◽  
Evaluation Of Learning

Social information retrieval systems, such as recommender systems, can benefit greatly from sharable and reusable evaluations of online resources. For example, in distributed repositories with rich collections of learning resources, users can benefit from evaluations, ratings, reviews, annotations, etc. that previous users have provided. Furthermore, sharing these evaluations and annotations can help attain the critical mass of data required for social information retrieval systems to be effective and efficient. This kind of interoperability requires a common framework that can be used to describe in a reusable manner the evaluation approach, as well as the results of the evaluation. This chapter discusses this concept, focusing on the rationale for a reusable and interoperable framework, that can be used to facilitate the representation, management and reuse of results from the evaluation of learning resources. For this purpose, we review a variety of evaluation approaches for learning resources, and study ways in which evaluation results may be characterised, so as to draw requirements for sharable and reusable evaluation metadata. Usage scenarios illustrate how evaluation metadata can be useful in the context of recommender systems for learning resources.

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