Dominant Meanings Approach Towards Individualized Web Search for Learning Environments

2008 ◽  
pp. 2376-2393
Author(s):  
M. A. Razek ◽  
C. Frasson
Keyword(s):  
Search Engines ◽  
Web Search ◽  
Individual Performance ◽  
Knowledge Bases ◽  
Specific Information ◽  
Intended Meaning ◽  
Web Based ◽  
Dominant Meaning ◽  
Web Based Learning ◽  
Adaptive Hypermedia Systems

This chapter describes how we can use dominant meaning to improve a Web-based learning environment. For sound adaptive hypermedia systems, we need updated knowledge bases from many kinds of resource (alternative explanations, examples, exercises, images, applets, etc.). The large amount of information available on the Web can play a prominent role in building these knowledge bases. Using the Internet without search engines to find specific information is like wandering aimlessly in the ocean and trying to catch a specific fish. It is obvious, however, that search engines are not intended to adapt to individual performance. Our new technique, based on dominant meaning, is used to individualize a query and search result. By dominant meaning, we refer to a set of keywords that best fits an intended meaning of the target word. Our experiments show that the dominant meanings approach greatly improves retrieval effectiveness.

Dominant Meanings Approach Towards Individualized Web Search for Learning Environments

2006 ◽  
pp. 46-69 ◽  
Author(s):  
Mohammed A. Razek ◽  
Claude Frasson ◽  
Marc Kaltenbach
Keyword(s):  
Search Engines ◽  
Web Search ◽  
Individual Performance ◽  
Knowledge Bases ◽  
Specific Information ◽  
Intended Meaning ◽  
Web Based ◽  
Dominant Meaning ◽  
Web Based Learning ◽  
Adaptive Hypermedia Systems

This chapter describes how we can use dominant meaning to improve a Web-based learning environment. For sound adaptive hypermedia systems, we need updated knowledge bases from many kinds of resource (alternative explanations, examples, exercises, images, applets, etc.). The large amount of information available on the Web can play a prominent role in building these knowledge bases. Using the Internet without search engines to find specific information is like wandering aimlessly in the ocean and trying to catch a specific fish. It is obvious, however, that search engines are not intended to adapt to individual performance. Our new technique, based on dominant meaning, is used to individualize a query and search result. By dominant meaning, we refer to a set of keywords that best fits an intended meaning of the target word. Our experiments show that the dominant meanings approach greatly improves retrieval effectiveness.

scholarly journals Conversion of Website Users to Customers-The Black Hat SEO Technique

2018 ◽  
Vol 8 (6) ◽  
pp. 29 ◽  
Author(s):  
Rotimi-Williams Bello ◽  
Firstman Noah Otobo
Keyword(s):  
Search Engines ◽  
Return On Investment ◽  
Web Search ◽  
Brand Awareness ◽  
The Internet ◽  
Search Query ◽  
Web Based ◽  
Search Results ◽  
Rank One ◽  
The Right

Search Engine Optimization (SEO) is a technique which helps search engines to find and rank one site over another in response to a search query. SEO thus helps site owners to get traffic from search engines. Although the basic principle of operation of all search engines is the same, the minor differences between them lead to major changes in results relevancy. Choosing the right keywords to optimize for is thus the first and most crucial step to a successful SEO campaign. In the context of SEO, keyword density can be used as a factor in determining whether a webpage is relevant to a specified keyword or keyword phrase. SEO is known for its contribution as a process that affects the online visibility of a website or a webpage in a web search engine's results. In general, the earlier (or higher ranked on the search results page), and more frequently a website appears in the search results list, the more visitors it will receive from the search engine's users; these visitors can then be converted into customers. It is the objective of this paper to re-present black hat SEO technique as an unprofessional but profitable method of converting website users to customers. Having studied and understood white hat SEO, black hat SEO, gray hat SEO, crawling, indexing, processing and retrieving methods used by search engines as a web software program or web based script to search for documents and files for keywords over the internet to return the list of results containing those keywords; it would be seen that proper application of SEO gives website a better user experience, SEO helps build brand awareness through high rankings, SEO helps circumvent competition, and SEO gives room for high increased return on investment.

scholarly journals Complementary Value of Databases for Discovery of Scholarly Literature: A User Survey of Online Searching for Publications in Art History

2010 ◽  
Vol 71 (3) ◽  
pp. 223-235 ◽  
Author(s):  
Erik Nemeth
Keyword(s):  
Search Engines ◽  
Web Search ◽  
Traditional Role ◽  
Online Searching ◽  
Web Based ◽  
Scholarly Literature ◽  
Specific Research ◽  
Web Search Engines ◽  
Complementary Value

Discovery of academic literature through Web search engines challenges the traditional role of specialized research databases. Creation of literature outside academic presses and peer-reviewed publications expands the content for scholarly research within a particular field. The resulting body of literature raises the question of whether scholars prefer the perceived broader access of Web search engines or opt for the precision of field-specific research databases. Surveys of art historians indicate a complementary use of online search tools with a reliance on field-specific research databases to discover authoritative content. Active use of Web search engines and initiatives for open access suggest that research databases will integrate into an evolving Web-based infrastructure that supports discovery and access of scholarly literature.

Leveraging Google Web Search Technology to Find Web-Based Learning Objects

2009 ◽  
Author(s):  
Cecilia Curlango-Rosas ◽  
Gregorio A. Ponce ◽  
Gabriel Lopez-Morteo ◽  
Monica Mendiola
Keyword(s):  
Web Search ◽  
Learning Objects ◽  
Web Based ◽  
Web Based Learning

Searching web documents using a summarization approach

2016 ◽  
Vol 12 (1) ◽  
pp. 83-101 ◽  
Author(s):  
Rani Qumsiyeh ◽  
Yiu-Kai Ng
Keyword(s):  
Search Engines ◽  
Web Search ◽  
Specific Information ◽  
Information Need ◽  
Search Query ◽  
Content Type ◽  
Additional Information ◽  
Search Results ◽  
User Query ◽  
Web Search Engines

Purpose The purpose of this paper is to introduce a summarization method to enhance the current web-search approaches by offering a summary of each clustered set of web-search results with contents addressing the same topic, which should allow the user to quickly identify the information covered in the clustered search results. Web search engines, such as Google, Bing and Yahoo!, rank the set of documents S retrieved in response to a user query and represent each document D in S using a title and a snippet, which serves as an abstract of D. Snippets, however, are not as useful as they are designed for, i.e. assisting its users to quickly identify results of interest. These snippets are inadequate in providing distinct information and capture the main contents of the corresponding documents. Moreover, when the intended information need specified in a search query is ambiguous, it is very difficult, if not impossible, for a search engine to identify precisely the set of documents that satisfy the user’s intended request without requiring additional information. Furthermore, a document title is not always a good indicator of the content of the corresponding document either. Design/methodology/approach The authors propose to develop a query-based summarizer, called QSum, in solving the existing problems of Web search engines which use titles and abstracts in capturing the contents of retrieved documents. QSum generates a concise/comprehensive summary for each cluster of documents retrieved in response to a user query, which saves the user’s time and effort in searching for specific information of interest by skipping the step to browse through the retrieved documents one by one. Findings Experimental results show that QSum is effective and efficient in creating a high-quality summary for each cluster to enhance Web search. Originality/value The proposed query-based summarizer, QSum, is unique based on its searching approach. QSum is also a significant contribution to the Web search community, as it handles the ambiguous problem of a search query by creating summaries in response to different interpretations of the search which offer a “road map” to assist users to quickly identify information of interest.

Panizzi, Lubetzky and Google: How the Modern Web Environment is Reinventing the Theory of Cataloguing

2013 ◽  
Author(s):  
D. Grant Campbell ◽  
Karl V. Fast
Keyword(s):  
University Students ◽  
Search Engines ◽  
Exploratory Study ◽  
Web Search ◽  
Knowledge Structure ◽  
The Other ◽  
Web Based ◽  
Web Environment ◽  
Other Hand ◽  
Web Search Engines

This paper uses cataloguing theory to interpret the partial results of an exploratory study of university students using Web search engines and Web-based OPACs. The participants expressed frustration with the OPAC; while they sensed that it was “organized,” they were unable to exploit that organization, and attributed their failure to the inadequacy of their own skills. In the Google searches, on the other hand, students were getting support traditionally advocated in catalogue design. Google gave them starting points: resources that broadly addressed their requirements, enabling them to get a greater sense of the knowledge structure that would help them to increase their precision in subsequent searches.Cette étude utilise la théorie du catalogage pour interpréter les résultats partiels d'une recherche exploratoire d'étudiants universitaires utilisant les moteurs de recherche Web et les catalogues publics en ligne. Les participants ont exprimé leur frustration envers les catalogues publics en ligne. Bien qu'ils percevaient que les catalogues sont "organisés", ils ont été incapables d’utiliser cette organisation et ont attribué leur échec au manque d'adaptation de leurs propres capacités. Lors de recherches avec Google, d'autre part, les étudiants ont reçu l’assistance traditionnellement proposée dans la conception d’un catalogue. Google leur a donné des points de départ : ressources qui répondent largement à leurs besoins, leur permettant ainsi d’obtenir une meilleure compréhension de la structure des connaissances qui pourraient les aider par la suite à augmenter leur précision lors de recherche. 

scholarly journals The Impact of Web Search Engines on Subject Searching in OPAC

2017 ◽  
Vol 23 (4) ◽  
pp. 168-180 ◽  
Author(s):  
Holly Yu ◽  
Margo Young
Keyword(s):  
Los Angeles ◽  
Search Engines ◽  
Web Search ◽  
State University ◽  
Web Based ◽  
Time Period ◽  
Online Catalogs ◽  
Major Increase ◽  
Web Search Engines ◽  
The Impact

This paper analyzes the results of transaction logs at California State University, Los Angeles (CSULA) and studies the effects of implementing a Web-based OPAC along with interface changes. The authors find that user success in subject searching remains problematic. A major increase in the frequency of searches that would have been more successful in resources other than the library catalog is noted over the time period 2000-2002. The authors attribute this increase to the prevalence of Web search engines and suggest that metasearching, relevance-ranked results, and relevance feedback ( "more like this") are now expected in user searching and should be integrated into online catalogs as search options.

A Case Study on Web-based Learning Environment Evaluation in Higher Education: Learner Perspectives in a Private University in Malaysia.

2020 ◽  
Vol 1 (2) ◽  
pp. 18-33
Author(s):  
Zarina Che Imbi ◽  
Tse-Kian Neo ◽  
Mai Neo
Keyword(s):  
Higher Education ◽  
Learning Environment ◽  
Private University ◽  
Systematic Evaluation ◽  
Digital Learning ◽  
Mixed Method Research ◽  
Web Based ◽  
Web Based Learning ◽  
Kirkpatrick’S Model

In the era of digital learning, multimedia-based classroom has been commonly used in higher education including Malaysian higher education institutions. A case study has been performed to evaluate web-based learning using Level 1 to 3 of Kirkpatrick's model in a multi-disciplinary course at Multimedia University, Malaysia. In this study, mixed method research was employed in which triangulation was performed from multiple sources of data collection to give deeper understanding. Students perceived that learning with multimedia was enjoyable. They were also motivated in learning and engaged through the use of web module as multimedia was perceived to motivate them and make learning fun. Students showed significant improvements in their knowledge based on the pre-test and post-test results on learning evaluation. Students were perceived to transfer the learning from web-based learning into the learning outcome. The systematic evaluation can provide the feedback that educators and institution as a whole need to improve the learning environment and programme quality. This study contributes to the research field by adding another perspective in evaluations of web-based learning. It also provides empirical evidence on student perspectives, learning and behaviour in a private university. It demonstrated that the Kirkpatrick's model is useful as an evaluation tool to be used in higher education.

Classification of means and methods of the Web semantic retrieval

2017 ◽  
pp. 030-050
Author(s):  
J.V. Rogushina ◽  
Keyword(s):  
Search Engines ◽  
Domain Knowledge ◽  
Information Needs ◽  
Web Search ◽  
User Interaction ◽  
Query Languages ◽  
Semantic Search ◽  
Semantic Retrieval ◽  
The Web

Problems associated with the improve ment of information retrieval for open environment are considered and the need for it’s semantization is grounded. Thecurrent state and prospects of development of semantic search engines that are focused on the Web information resources processing are analysed, the criteria for the classification of such systems are reviewed. In this analysis the significant attention is paid to the semantic search use of ontologies that contain knowledge about the subject area and the search users. The sources of ontological knowledge and methods of their processing for the improvement of the search procedures are considered. Examples of semantic search systems that use structured query languages (eg, SPARQL), lists of keywords and queries in natural language are proposed. Such criteria for the classification of semantic search engines like architecture, coupling, transparency, user context, modification requests, ontology structure, etc. are considered. Different ways of support of semantic and otology based modification of user queries that improve the completeness and accuracy of the search are analyzed. On base of analysis of the properties of existing semantic search engines in terms of these criteria, the areas for further improvement of these systems are selected: the development of metasearch systems, semantic modification of user requests, the determination of an user-acceptable transparency level of the search procedures, flexibility of domain knowledge management tools, increasing productivity and scalability. In addition, the development of means of semantic Web search needs in use of some external knowledge base which contains knowledge about the domain of user information needs, and in providing the users with the ability to independent selection of knowledge that is used in the search process. There is necessary to take into account the history of user interaction with the retrieval system and the search context for personalization of the query results and their ordering in accordance with the user information needs. All these aspects were taken into account in the design and implementation of semantic search engine "MAIPS" that is based on an ontological model of users and resources cooperation into the Web.

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