The Effect of Web Search Result Display on Users’ Perceptual Experience and Information Seeking Performance

2017 ◽  
Vol 59 (1) ◽  
pp. 10-18 ◽  
Author(s):  
Hosam Al-Samarraie ◽  
Ahmed Isam Al-Hatem
2012 ◽  
pp. 411-437
Author(s):  
Stéphane Chaudiron ◽  
Madjid Ihadjadene

This chapter shows that the wider use of Web search engines, reconsidering the theoretical and methodological frameworks to grasp new information practices. Beginning with an overview of the recent challenges implied by the dynamic nature of the Web, this chapter then traces the information behavior related concepts in order to present the different approaches from the user perspective. The authors pay special attention to the concept of “information practice” and other related concepts such as “use”, “activity”, and “behavior” largely used in the literature but not always strictly defined. The authors provide an overview of user-oriented studies that are meaningful to understand the different contexts of use of electronic information access systems, focusing on five approaches: the system-oriented approaches, the theories of information seeking, the cognitive and psychological approaches, the management science approaches, and the marketing approaches. Future directions of work are then shaped, including social searching and the ethical, cultural, and political dimensions of Web search engines. The authors conclude considering the importance of Critical theory to better understand the role of Web Search engines in our modern society.


2018 ◽  
pp. 4661-4666
Author(s):  
Xuehua Shen ◽  
Cheng Xiang Zhai
Keyword(s):  

Author(s):  
Iris Xie

The emergence of the Internet has allowed millions of people to use a variety of electronic information retrieval (IR) systems, such as digital libraries, Web search engines, online databases, and Online Public Access Catalogues (OPACs). The nature of IR is interaction. Interactive information retrieval is defined as the communication process between the users and the IR systems. However, the dynamics of interactive IR is not yet fully understood. Moreover, most of the existing IR systems do not support the full range of users’ interactions with IR systems. Instead, they only support one type of information-seeking strategy: how to specify queries by using terms to select relevant information. However, new digital environments require users to apply multiple information-seeking strategies and shift from one information- seeking strategy to another in the information retrieval process.


2018 ◽  
Vol 7 (3.3) ◽  
pp. 90
Author(s):  
Sumathi Rani Manukonda ◽  
Asst.Prof Kmit ◽  
Narayanguda . ◽  
Hyderabad . ◽  
Nomula Divya ◽  
...  

Clustering the document in data mining is one of the traditional approach in which the same documents that are more relevant are grouped together. Document clustering take part in achieving accuracy that retrieve information for systems that identifies the nearest neighbors of the document. Day to day the massive quantity of data is being generated and it is clustered. According to particular sequence to improve the cluster qualityeven though different clustering methods have been introduced, still many challenges exist for the improvement of document clustering. For web search purposea document in group is efficiently arranged for the result retrieval.The users accordingly search query in an organized way. Hierarchical clustering is attained by document clustering.To the greatest algorithms for groupingdo not concentrate on the semantic approach, hence resulting to the unsatisfactory output clustering. The involuntary approach of organizing documents of web like Google, Yahoo is often considered as a reference. A distinct method to identify the existing group of similar things in the previously organized documents and retrieves effective document classifier for new documents. In this paper the main concentration is on hierarchical clustering and k-means algorithms, hence prove that k-means and its variant are efficient than hierarchical clustering along with this by implementing greedy fast k-means algorithm (GFA) for cluster document in efficient way is considered.  


2009 ◽  
pp. 3501-3506 ◽  
Author(s):  
Ronny Lempel ◽  
Fabrizio Silvestri
Keyword(s):  

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