MARS

Web Mining ◽  
2011 ◽  
pp. 99-118 ◽  
Author(s):  
Xiannong Meng ◽  
Zhixiang Chen
Keyword(s):  
Search Engine ◽  
Relevance Feedback ◽  
Adaptive Algorithm ◽  
User Preference ◽  
Adaptive Refinement ◽  
Search Performance ◽  
Web Searches ◽  
Expansion Strategy ◽  
Information Preference ◽  
Feedback Algorithm

This chapter reports the project MARS (Multiplicative Adaptive Refinement Search), which applies a new multiplicative adaptive algorithm for user preference retrieval to Web searches. The new algorithm uses a multiplicative query expansion strategy to adaptively improve and reformulate the query vector to learn users’ information preference. The algorithm has provable better performance than the popular Rocchio’s similarity-based relevance feedback algorithm in learning a user preference that is determined by a linear classifier with a small number of non-zero coefficients over the real-valued vector space. A meta-search engine based on the aforementioned algorithm is built, and analysis of its search performance is presented.

Search Engine Update

2001 ◽  
Vol 1 (3) ◽  
pp. 28-31 ◽  
Author(s):  
Valerie Stevenson
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Search Strategy ◽  
Search Strategies ◽  
Boolean Logic ◽  
Web Searches ◽  
Search Techniques ◽  
Looking Back ◽  
The Web

Looking back to 1999, there were a number of search engines which performed equally well. I recommended defining the search strategy very carefully, using Boolean logic and field search techniques, and always running the search in more than one search engine. Numerous articles and Web columns comparing the performance of different search engines came to different conclusions on the ‘best’ search engines. Over the last year, however, all the speakers at conferences and seminars I have attended have recommended Google as their preferred tool for locating all kinds of information on the Web. I confess that I have now abandoned most of my carefully worked out search strategies and comparison tests, and use Google for most of my own Web searches.

How Interface Design and Search Strategy Influence Children’s Search Performance and Evaluation

2014 ◽  
pp. 241-287 ◽  
Author(s):  
Hanna Jochmann-Mannak ◽  
Leo Lentz ◽  
Theo Huibers ◽  
Ted Sanders
Keyword(s):  
Search Engine ◽  
Interface Design ◽  
Search Strategy ◽  
Emotional Valence ◽  
Affective Responses ◽  
Visual Design ◽  
Search Performance ◽  
Different Types ◽  
Navigation Structure ◽  
Performance And Evaluation

This chapter presents an experiment with 158 children, aged 10 to 12, in which search performance and attitudes towards an informational Website are investigated. The same Website was designed in 3 different types of interface design varying in playfulness of navigation structure and in playfulness of visual design. The type of interface design did not have an effect on children’s search performance, but it did influence children’s feelings of emotional valence and their evaluation of “goodness.” Children felt most positive about the Website with a classical navigation structure and playful aesthetics. They found the playful image map Website least good. More importantly, children’s search performance was much more effective and efficient when using the search engine than when browsing the menu. Furthermore, this chapter explores the challenge of measuring affective responses towards digital interfaces with children by presenting an elaborate evaluation of different methods.

Uncertain Confidence Network-Based Collaborative Information Retrieval Relevance Feedback Algorithm

2020 ◽  
pp. 20-39
Author(s):  
Fatiha Naouar ◽  
Lobna Hlaoua ◽  
Mohamed Nazih Omri
Keyword(s):  
Information Retrieval ◽  
Relevance Feedback ◽  
Information Source ◽  
Strong Association ◽  
Relevant Information ◽  
User Query ◽  
Proposed Model ◽  
Evidence Source ◽  
Feedback Algorithm ◽  
Collaborative Information Retrieval

Collaborative retrieval allows increasing the amount of relevant information found and sharing history with others. The collaborative retrieval can reduce the retrieval time performed by the users of the same profile. This chapter proposes a new relevance feedback algorithm to collaborative information retrieval based on a confidence network, which performs propagation relevance between annotations terms. The main contribution in this work is the extraction of relevant terms to reformulate the initial user query considering the annotations as an information source. The proposed model introduces the concept of necessity that allows determining the terms that have strong association relationships estimated to the measure of a confidence. Since the user is overwhelmed by a variety of contradictory annotations, another contribution consists of determining the relevant annotations for a given evidence source. The experimental study gives very encouraging results.

Searching for Information on the World Wide Web with a Search Engine: A Pilot Study on Cognitive Flexibility in Younger and Older Users

2010 ◽  
Vol 106 (2) ◽  
pp. 490-498 ◽  
Author(s):  
Aurelie Dommes ◽  
Aline Chevalier ◽  
Marilyne Rossetti
Keyword(s):  
Pilot Study ◽  
World Wide Web ◽  
Search Engine ◽  
Cognitive Flexibility ◽  
World Wide ◽  
Search Method ◽  
Web Searches ◽  
Younger Adults ◽  
Age Related ◽  
The World

This pilot study investigated the age-related differences in searching for information on the World Wide Web with a search engine. 11 older adults (6 men, 5 women; M age = 59 yr., SD = 2.76, range = 55–65 yr.) and 12 younger adults (2 men, 10 women; M = 23.7 yr., SD = 1.07, range = 22–25 yr.) had to conduct six searches differing in complexity, and for which a search method was or was not induced. The results showed that the younger and older participants provided with an induced search method were less flexible than the others and produced fewer new keywords. Moreover, older participants took longer than the younger adults, especially in the complex searches. The younger participants were flexible in the first request and spontaneously produced new keywords (spontaneous flexibility), whereas the older participants only produced new keywords when confronted by impasses (reactive flexibility). Aging may influence web searches, especially the nature of keywords used.

scholarly journals Improving the Results of Google Scholar Engine through Automatic Query Expansion Mechanism and Pseudo Re-ranking using MVRA

2018 ◽  
Vol 42 (2) ◽  
pp. 219-229
Author(s):  
Mawloud Mosbah
Keyword(s):  
Image Retrieval ◽  
Relevance Feedback ◽  
Query Expansion ◽  
Majority Voting ◽  
Google Scholar ◽  
Content Based Image Retrieval ◽  
Ranking Algorithm ◽  
Expansion Mechanism ◽  
Feedback Algorithm ◽  
Pseudo Relevance Feedback

In this paper, we address the enhancing of Google Scholar engine, in the context of text retrieval, through two mechanisms related to the interrogation protocol of that query expansion and reformulation. The both schemes are applied with re-ranking results using a pseudo relevance feedback algorithm that we have proposed previously in the context of Content based Image Retrieval (CBIR) namely Majority Voting Re-ranking Algorithm (MVRA). The experiments conducted using ten queries reveal very promising results in terms of effectiveness.

scholarly journals Eysenbach, Tuische and Diepgen’s Evaluation of Web Searching for Identifying Unpublished Studies for Systematic Reviews: An Innovative Study Which is Still Relevant Today

2016 ◽  
Vol 11 (3) ◽  
pp. 108
Author(s):  
Simon Briscoe
Keyword(s):  
Systematic Review ◽  
Clinical Trials ◽  
Search Engine ◽  
Systematic Reviews ◽  
Search Engines ◽  
Web Search ◽  
Web Searching ◽  
Web Searches ◽  
Web Search Engine ◽  
Unpublished Studies

A Review of: Eysenbach, G., Tuische, J. & Diepgen, T.L. (2001). Evaluation of the usefulness of Internet searches to identify unpublished clinical trials for systematic reviews. Medical Informatics and the Internet in Medicine, 26(3), 203-218. http://dx.doi.org/10.1080/14639230110075459 Objective – To consider whether web searching is a useful method for identifying unpublished studies for inclusion in systematic reviews. Design – Retrospective web searches using the AltaVista search engine were conducted to identify unpublished studies – specifically, clinical trials – for systematic reviews which did not use a web search engine. Setting – The Department of Clinical Social Medicine, University of Heidelberg, Germany. Subjects – n/a Methods – Pilot testing of 11 web search engines was carried out to determine which could handle complex search queries. Pre-specified search requirements included the ability to handle Boolean and proximity operators, and truncation searching. A total of seven Cochrane systematic reviews were randomly selected from the Cochrane Library Issue 2, 1998, and their bibliographic database search strategies were adapted for the web search engine, AltaVista. Each adaptation combined search terms for the intervention, problem, and study type in the systematic review. Hints to planned, ongoing, or unpublished studies retrieved by the search engine, which were not cited in the systematic reviews, were followed up by visiting websites and contacting authors for further details when required. The authors of the systematic reviews were then contacted and asked to comment on the potential relevance of the identified studies. Main Results – Hints to 14 unpublished and potentially relevant studies, corresponding to 4 of the 7 randomly selected Cochrane systematic reviews, were identified. Out of the 14 studies, 2 were considered irrelevant to the corresponding systematic review by the systematic review authors. The relevance of a further three studies could not be clearly ascertained. This left nine studies which were considered relevant to a systematic review. In addition to this main finding, the pilot study to identify suitable search engines found that AltaVista was the only search engine able to handle the complex searches required to search for unpublished studies. Conclusion –Web searches using a search engine have the potential to identify studies for systematic reviews. Web search engines have considerable limitations which impede the identification of studies.

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