Guiding Students in Finding information on the Web

1999 ◽  
Vol 62 (3) ◽  
pp. 57-70
Author(s):  
Zane K. Quible
Keyword(s):  
Search Engines ◽  
Web Search ◽  
Business Communication ◽  
Boolean Logic ◽  
Search Process ◽  
The Right ◽  
The Web ◽  
Infor Mation

Searching for information on the Web can be a daunting, frustrating, mind-bog gling, and sometimes-futile activity. To increase the odds of finding the right infor mation, one needs to understand the operation of four search tools: Web directo ries, search engines, indexes, and spiders or robots. Understanding Boolean logic also helps. Business communication instructors can aid students in their research by introducing them to the terminology and functions of an efficient Web search process.

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.

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.

scholarly journals Web Search Engines - Not Yet a Reliable Replacement for Bibliographic Databases

2018 ◽  
Vol 13 (3) ◽  
pp. 85-87
Author(s):  
Emma Hughes
Keyword(s):  
Social Sciences ◽  
Social Services ◽  
Search Engines ◽  
English Language ◽  
Web Search ◽  
Boolean Logic ◽  
Bibliographic Databases ◽  
Quality Of Reporting ◽  
Health And Social Care ◽  
Web Search Engines

A Review of: Bates, J., Best, P., McQuilkin, J., & Taylor, B. (2017) Will web search engines replace bibliographic databases in the systematic identification of research? The Journal of Academic Librarianship, 43(1), 8-17. https://doi.org/10.1016/j.acalib.2016.11.003 Abstract Objective - To explore whether web search engines could replace bibliographic databases in retrieving research. Design - Systematic review. Setting - English language articles in health and social care; comparing bibliographic databases and web search engines for retrieving research published between January 2005 and August 2015, in peer-reviewed journals and available in full-text. Subjects - Eight bibliographic databases: ASSIA (Applied Social Sciences Index and Abstracts), CINAHL Plus (Cumulative Index to Nursing and Allied Health Literature), LISA (Library and Information Science Abstracts), Medline, PsycInfo, Scopus, SSA (Social Services Abstracts), and SSCI (Social Sciences Citation Index) and five web search engines: Ask, Bing, Google, Google Scholar, Yahoo. Methods - A literature search via the above bibliographic databases and web search engines. The retrieved results were independently appraised by two researchers, using a combination of tools and checklists, including the PRESS checklist (McGowan et al., 2016) and took guidance on developing search strategies from the Centre for Reviews and Dissemination (2009). Main Results - Sixteen papers met the appraisal requirements. Each paper compared at least one bibliographic database against one web-search engine. The authors also discuss findings from their own search process. Precision and sensitivity scores from each paper were compared. The results highlighted that web search engines do not necessarily use Boolean logic and in general have limited functionality compared to bibliographic databases. There were variances in the way precision scores were calculated between papers, but when based on the first 100 results, web search engines were similar to some databases. However, their sensitivity scores were much weaker. Conclusion - Whilst precision scores were strong for web search engines, sensitivity was lacking; therefore web search engines cannot be seen as a replacement for bibliographic databases at this time. The authors recommend improving the quality of reporting in studies regarding literature searching in academia in order for reliable comparisons to be made.

A Roadmap to Integrate Document Clustering in Information Retrieval

2013 ◽  
pp. 31-45
Author(s):  
R. Subhashini ◽  
V.Jawahar Senthil Kumar
Keyword(s):  
Information Retrieval ◽  
Search Engines ◽  
World Wide ◽  
Clustering Algorithm ◽  
Web Search ◽  
Full Potential ◽  
Digital Information ◽  
Search Results ◽  
The World ◽  
The Web

The World Wide Web is a large distributed digital information space. The ability to search and retrieve information from the Web efficiently and effectively is an enabling technology for realizing its full potential. Information Retrieval (IR) plays an important role in search engines. Today’s most advanced engines use the keyword-based (“bag of words”) paradigm, which has inherent disadvantages. Organizing web search results into clusters facilitates the user’s quick browsing of search results. Traditional clustering techniques are inadequate because they do not generate clusters with highly readable names. This paper proposes an approach for web search results in clustering based on a phrase based clustering algorithm. It is an alternative to a single ordered result of search engines. This approach presents a list of clusters to the user. Experimental results verify the method’s feasibility and effectiveness.

How People Search for Governmental Information on the Web

2011 ◽  
pp. 933-939
Author(s):  
B. J. Jansen ◽  
A. Spink
Keyword(s):  
Web Sites ◽  
Search Engines ◽  
Web Search ◽  
Daily Lives ◽  
Governmental Organizations ◽  
Web Search Engines ◽  
People Search ◽  
E Mail ◽  
The U.S ◽  
The Web

People are now confronted with the task of locating electronic information needed to address the issues of their daily lives. The Web is presently the major information source for many people in the U.S. (Cole, Suman, Schramm, Lunn, & Aquino, 2003), used more than newspapers, magazines, and television as a source of information. Americans are expanding their use of the Web for all sorts of information and commercial purposes (Horrigan, 2004; Horrigan & Rainie, 2002; National Telecommunications and Information Administration, 2002). Searching for information is one of the most popular Web activities, second only to the use of e-mail (Nielsen Media, 1997). However, successfully locating needed information remains a difficult and challenging task (Eastman & Jansen, 2003). Locating relevant information not only affects individuals but also commercial, educational, and governmental organizations. This is especially true in regards to people interacting with their governmental agencies. Executive Order 13011 (Clinton, 1996) directed the U.S. federal government to move aggressively with strategies to utilize the Internet. Birdsell and Muzzio (1999) present the growing presence of governmental Web sites, classifying them into three general categories, (1) provision of information, (2) delivery of forms, and (3) transactions. In 2004, 29% of American said they visited a government Web site to contact some governmental entity, 18% sent an e-mail and 22% use multiple means (Horrigan, 2004). It seems clear that the Web is a major conduit for accessing governmental information and maybe services. Search engines are the primary means for people to locate Web sites (Nielsen Media, 1997). Given the Web’s importance, we need to understand how Web search engines perform (Lawrence & Giles, 1998) and how people use and interact with Web search engines to locate governmental information. Examining Web searching for governmental information is an important area of research with the potential to increase our understanding of users of Web-based governmental information, advance our knowledge of Web searchers’ governmental information needs, and positively impact the design of Web search engines and sites that specialize in governmental information.

Deep Web

2009 ◽  
pp. 581-588 ◽  
Author(s):  
Denis Shestakov
Keyword(s):  
Search Engines ◽  
Large Scale ◽  
Web Search ◽  
Web Database ◽  
Web Search Engine ◽  
Search Form ◽  
Complete Set ◽  
Web Crawlers ◽  
Pass Through ◽  
The Web

Finding information on the Web using a web search engine is one of the primary activities of today’s web users. For a majority of users results returned by conventional search engines are an essentially complete set of links to all pages on the Web relevant to their queries. However, currentday searchers do not crawl and index a significant portion of the Web and, hence, web users relying on search engines only are unable to discover and access a large amount of information from the nonindexable part of the Web. Specifically, dynamic pages generated based on parameters provided by a user via web search forms are not indexed by search engines and cannot be found in searchers’ results. Such search interfaces provide web users with an online access to myriads of databases on the Web. In order to obtain some information from a web database of interest, a user issues his/her query by specifying query terms in a search form and receives the query results, a set of dynamic pages which embed required information from a database. At the same time, issuing a query via an arbitrary search interface is an extremely complex task for any kind of automatic agents including web crawlers, which, at least up to the present day, do not even attempt to pass through web forms on a large scale.

scholarly journals Enhancing the performance of search engines based heap based data file and hash based indexing file

2018 ◽  
Vol 7 (2.7) ◽  
pp. 372
Author(s):  
Dr Jkr Sastry ◽  
Chandu Sai Chittibomma ◽  
Thulasi Manohara Reddy Alla
Keyword(s):  
Search Engines ◽  
Data File ◽  
Search Process ◽  
Indexing Method ◽  
Storage Area ◽  
The Web

WEB clients use the WEB for searching the content that they are looking for through inputting keywords or snippets as input to the search engines. Search Engines follows a process to collect the content and provide the same as output in terms of URL links. Sometimes enormous time is taken to fetch the content fetched especially when it goes into number of display pages. Locating the content among the number of pages of URLS displayed is complex. Proper indexing method will help in reducing the number of display pages and enhances the seed of processing and result into reducing the size of index space.In this paper a non-clustered indexing method based on hash based indexing and when the data is stored as a heap file is presented that helps the entire search process quite fast requiring very less storage area. 

What is popular on Wikipedia and why?

First Monday ◽  
2007 ◽  
Author(s):  
Anselm Spoerri
Keyword(s):  
Search Engines ◽  
Web Search ◽  
Search Behavior ◽  
Search Queries ◽  
Search Results ◽  
The Web

This paper analyzes which pages and topics are the most popular on Wikipedia and why. For the period of September 2006 to January 2007, the 100 most visited Wikipedia pages in a month are identified and categorized in terms of the major topics of interest. The observed topics are compared with search behavior on the Web. Search queries, which are identical to the titles of the most popular Wikipedia pages, are submitted to major search engines and the positions of popular Wikipedia pages in the top 10 search results are determined. The presented data helps to explain how search engines, and Google in particular, fuel the growth and shape what is popular on Wikipedia.

scholarly journals Conceptual displacement: Web search as a learning experience

2021 ◽  
Vol 5 (38) ◽  
pp. 1-16
Author(s):  
Martha Vidal Sepúlveda ◽  
Gabriel Valdés León ◽  
Christian Olivares Rodríguez
Keyword(s):  
Web Search ◽  
Learning Experience ◽  
Search Process ◽  
Lexical Information ◽  
Research Task ◽  
Quasi Experimental ◽  
Last Stage ◽  
The Relationship ◽  
The Web ◽  
Quantitative Nature

The research aims to identify the relationship between the behavior of seeking information on the Internet to solve a research task and the answers given by a group of university students. To do this, a quasi-experimental study was designed, of a quantitative nature, in which both the words used in the web search process and the answers made from it were analyzed. The data was processed thanks to the use of the GoNSA2 platform, which allows monitoring the search process, and the Iramuteq software, oriented towards the analysis of lexical information. Among the main results, we highlight a shift between the topics used in the search and those observed in the response stage and an increase in the categories present in this last stage, which allows considering the search process as an instance of learning.

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