Clustering hypertext with applications to web searching

2000 ◽  
Author(s):  
Dharmendra S. Modha ◽  
W. Scott Spangler
Keyword(s):  
Web Searching

Review of Improvement of Web Search Based on Web Log File

2012 ◽  
Vol 3 (2) ◽  
pp. 298-300 ◽  
Author(s):  
Soniya P. Chaudhari ◽  
Prof. Hitesh Gupta ◽  
S. J. Patil
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Web Search ◽  
Pattern Mining ◽  
Efficiency Improvement ◽  
Web Searching ◽  
Important Method ◽  
Web Log ◽  
Journal Paper ◽  
Log File

In this paper we review various research of journal paper as Web Searching efficiency improvement. Some important method based on sequential pattern Mining. Some are based on supervised learning or unsupervised learning. And also used for other method such as Fuzzy logic and neural network

Web searching for daily living

2009 ◽  
Author(s):  
Takuya Maekawa ◽  
Yutaka Yanagisawa ◽  
Yasushi Sakurai ◽  
Yasue Kishino ◽  
Koji Kamei ◽  
...  
Keyword(s):  
Daily Living ◽  
Web Searching

A temporal comparison of AltaVista Web searching

2005 ◽  
Vol 56 (6) ◽  
pp. 559-570 ◽  
Author(s):  
Bernard J. Jansen ◽  
Amanda Spink ◽  
Jan Pedersen
Keyword(s):  
Web Searching ◽  
Temporal Comparison

Web searching in a multilingual world

2008 ◽  
Vol 51 (5) ◽  
pp. 32-40 ◽  
Author(s):  
Wingyan Chung
Keyword(s):  
Web Searching

A Measure of Similarity between Graph Vertices: Applications to Synonym Extraction and Web Searching

SIAM Review ◽  
2004 ◽  
Vol 46 (4) ◽  
pp. 647-666 ◽  
Author(s):  
Vincent D. Blondel ◽  
Anahí Gajardo ◽  
Maureen Heymans ◽  
Pierre Senellart ◽  
Paul Van Dooren
Keyword(s):  
Web Searching ◽  
Measure Of Similarity

In quest of goldilocks ranges in searching for information on the web

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anna Matysek ◽  
Jacek Tomaszczyk
Keyword(s):  
Information Search ◽  
Design Methodology ◽  
Search Task ◽  
Web Searching ◽  
Content Type ◽  
Scientific Disciplines ◽  
Preliminary Study ◽  
The Right ◽  
User Experiment ◽  
Practical Implications

PurposeThe quest to discover optimal conditions or amounts has been carried out in many scientific disciplines and practical fields. In astrophysics, biology, medicine, psychology and education, the quest has resulted in finding the right amount of something, a desirable middle between extremes, a balance between conditions or the optimal state of a system. The results are referred to as the Goldilocks principle, which is based on the idea of being “just right”. The aim of our study was to find out if there are any measures in information search that could be identified as Goldilocks ranges.Design/methodology/approachWe conducted a user experiment in which 68 participants carried out a time-unlimited, topical search task involving finding relevant websites on the basis of which the participants were supposed to prepare a presentation on a given topic. We examined aspects of their search behavior.FindingsWe found that information search Goldilocks ranges can be identified for a length of a search session, number of relevant results, number of queries submitted and number of search engine results pages (SERPs) visited. This preliminary study has resulted in indicating the following dominant ranges: Number of relevant documents found: 5–8; Time spent searching: 21–35 min; Number of queries submitted: 3–7; Number of SERPs viewed: 1–3.Originality/valueTill now, no one has studied Goldilocks ranges in information retrieval. The Goldilocks ranges have some practical implications for improving the effectiveness of web searching.

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