Visualizing Search Results: Engineering Visual Patterns Development for the Web

2012 ◽  
pp. 127-142 ◽  
Author(s):  
Rober Morales-Chaparro ◽  
Juan Carlos Preciado ◽  
Fernando Sánchez-Figueroa
Keyword(s):  
Search Results ◽  
Visual Patterns ◽  
The Web

scholarly journals Resources and Capabilities from Their Very Outset: a Bibliometric Comparison Between Scopus and the Web of Science

2018 ◽  
Vol 10 (4) ◽  
pp. 1
Author(s):  
Mileidy Alvarez-Melgarejo ◽  
Martha L. Torres-Barreto
Keyword(s):  
Web Of Science ◽  
Bibliographic Databases ◽  
Scientific Publications ◽  
Bibliometric Method ◽  
Search Results ◽  
Resources And Capabilities ◽  
New Research ◽  
The Relationship ◽  
The Web

The bibliometric method has proven to be a powerful tool for the analysis of scientific publications, in such a way that allows rating the quality of the knowledge generating process, as well as its impact on firm´s environment. This article presents a comparison between two powerful bibliographic databases in terms of their coverage and the usefulness of their content. The comparison starts with a subject associated to the relationship between resources and capabilities. The outcomes show that the search results differ between both databases. The Web Of Science (WOS), has a greater coverage than SCOPUS has.  It also has a greater impact in terms of most cited authors and publications. The search results in the WOS yield articles from 2001, while Scopus yields articles from 1976, however, some of the latter are inconsistent with the topic being searched. The analysis points to a lack of studies regarding resources as foundations of firm´s capabilities; as a result, new research on this field is suggested.

Category-Based Interfaces for Mobile Search

2015 ◽  
pp. 75-104
Author(s):  
Tomi Heimonen
Keyword(s):  
User Study ◽  
Information Access ◽  
Future Research ◽  
Information Need ◽  
Research Directions ◽  
Search Results ◽  
Future Research Directions ◽  
Mobile Context ◽  
The Web

One of the challenges with designing effective mobile search interfaces is how to present and explore the search results. Category-based result organization and presentation techniques have been suggested in literature as a complement to the traditional ranked result list. In the mobile context categories can facilitate information access by providing an overview of the result set, by reducing the need for keyword entry and by providing means to filter the results. This chapter includes a review of recent research on category-based interfaces for mobile search. The chapter also addresses the challenges of evaluating mobile search in situ and presents a longitudinal user study that investigated how a mobile clustering interface is used to search the Web. Results from the study show that category-based interaction can be situationally useful, for example when users have problems describing their information need or wish to retrieve a subset of results. In summary, the chapter proposes future research directions for category-based mobile search interfaces.

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.

User Models for Adaptive Information Retrieval on the Web

2012 ◽  
Vol 3 (3) ◽  
pp. 1-19
Author(s):  
Max Chevalier ◽  
Christine Julien ◽  
Chantal Soulé-Dupuy
Keyword(s):  
Information Retrieval ◽  
Search Engines ◽  
User Profile ◽  
User Model ◽  
User Models ◽  
Search Results ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Adaptive Information Retrieval ◽  
The Web

Searching information can be realized thanks to specific tools called Information Retrieval Systems IRS (also called “search engines”). To provide more accurate results to users, most of such systems offer personalization features. To do this, each system models a user in order to adapt search results that will be displayed. In a multi-application context (e.g., when using several search engines for a unique query), personalization techniques can be considered as limited because the user model (also called profile) is incomplete since it does not exploit actions/queries coming from other search engines. So, sharing user models between several search engines is a challenge in order to provide more efficient personalization techniques. A semantic architecture for user profile interoperability is proposed to reach this goal. This architecture is also important because it can be used in many other contexts to share various resources models, for instance a document model, between applications. It is also ensuring the possibility for every system to keep its own representation of each resource while providing a solution to easily share it.

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.

OPTIMASI RISET KEYWORD DENGAN TEKNIK ALLINTITLLE PADA MESIN PENCARI GOOGLE

2018 ◽  
Vol 1 (1) ◽  
pp. 1-5
Author(s):  
Hengki Tamando Sihotang
Keyword(s):  
Search Engine ◽  
Information Needs ◽  
Research Question ◽  
Online Information ◽  
Web Based ◽  
Development Method ◽  
Government Services ◽  
Search Results ◽  
Google Search ◽  
The Web

Online information needs have evolved in the real direction. These needs include the latest information, government services, and commercial products. The research question is how to describe and optimize keyword research with the allintitle technique on the google search engine. The development method used in this research is the prototype method because it is considered able to be evaluated directly on the user. The system testing is done for 3 months by placing keywords on several websites on Google. The conclusion that can be taken is to use the allintitle technique, the search results for the web are easier to find. And this web-based allintitle technique can overcome the challenges of captcha verification from the Google search engine.   Keywords: Allintitle, Google's Search Engine, Keyword competition.

BEYOND RANKED LISTS IN WEB SEARCH: AGGREGATING WEB CONTENT INTO TOPIC PAGES

2010 ◽  
Vol 04 (04) ◽  
pp. 509-534 ◽  
Author(s):  
NIRANJAN BALASUBRAMANIAN ◽  
SILVIU CUCERZAN
Keyword(s):  
Web Search ◽  
Automatic Generation ◽  
Selection Method ◽  
Web Content ◽  
Search Results ◽  
Aggregate Information ◽  
Search Logs ◽  
The Web

We investigate the automatic generation of topic pages as an alternative to the current Web search paradigm. Topic pages explicitly aggregate information across documents, filter redundancy, and promote diversity of topical aspects. We propose a novel framework for building rich topical aspect models and selecting diverse information from the Web. In particular, we use Web search logs to build aspect models with various degrees of specificity, and then employ these aspect models as input to a sentence selection method that identifies relevant and non-redundant sentences from the Web. Automatic and manual evaluations on biographical topics show that topic pages built by our system compare favorably to regular Web search results and to MDS-style summaries of the Web results on all metrics employed.

WEBYACHT: A CONCEPT-BASED SEARCH TOOL FOR WWW

1999 ◽  
Vol 08 (02) ◽  
pp. 137-156 ◽  
Author(s):  
CHING-CHI HSU ◽  
CHIA-HUI CHANG
Keyword(s):  
Information Search ◽  
Relevance Feedback ◽  
Web Search ◽  
Automatic Assessment ◽  
Feedback Mechanisms ◽  
Document Ranking ◽  
Search Results ◽  
Web Information ◽  
Search Tool ◽  
The Web

This paper describes a Web information search tool called WebYacht. The goal of WebYacht is to solve the problem of imprecise search results in current Web search engines. Due to incomplete information given by users and the diversified information published on the Web, conventional document ranking based on an automatic assessment of document relevance to the query may not be the best approach when little information is given as in most cases. In order to clarify the ambiguity of the short queries given by users, WebYacht adopts cluster-based browsing model as well as relevance feedback to facilitate Web information search. The idea is to have users give two to three times more feedback in the same amount of time that would be required to give feedback for conventional feedback mechanisms. With the assistance of cluster-based representation provided by WebYacht, a lot of browsing labor can be reduced. In this paper, we explain the techniques used in the design of WebYacht and compare the performances of feedback interface designs and to conventional similarity ranking search results.

scholarly journals Marketing Digital na Recuperação da Informação: técnicas de SEO para visibilidade de periódico científico

2020 ◽  
pp. 133-143
Author(s):  
Barbara Coelho Neves ◽  
Ramon Davi Santana ◽  
Dulcinéia Vieira de Assunção Gomes
Keyword(s):  
Literature Review ◽  
Search Engine ◽  
Scientific Production ◽  
Qualitative Approach ◽  
Digital Marketing ◽  
Scientific Journals ◽  
Global Level ◽  
Technical Aspects ◽  
Search Results ◽  
The Web

It deals with digital marketing through the search engine optimization (SEO) techniques applied to the case of a scientific magazine's website. It analyzes objective and technical aspects and measures of SEO that promote the leverage of the visibility of the website and its published content among the main search results in search engines. The method is descriptive, with a qualitative approach and the support of literature review. As a result, the text presents in a descriptive and reasoned way a brief analysis from the perspective of on-site and on-page SEO. It is concluded that the websites of scientific journals can benefit from SEO techniques in the context of information retrieval. The non-use of basic SEO techniques corroborates for a potential invisibility or low recovery of scientific production on the Web in search engine results at a global level.

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