scholarly journals State-of-the-Art Review on Relevance of Genetic Algorithm to Internet Web Search

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Kehinde Agbele ◽  
Ademola Adesina ◽  
Daniel Ekong ◽  
Oluwafemi Ayangbekun

People use search engines to find information they desire with the aim that their information needs will be met. Information retrieval (IR) is a field that is concerned primarily with the searching and retrieving of information in the documents and also searching the search engine, online databases, and Internet. Genetic algorithms (GAs) are robust, efficient, and optimizated methods in a wide area of search problems motivated by Darwin’s principles of natural selection and survival of the fittest. This paper describes information retrieval systems (IRS) components. This paper looks at how GAs can be applied in the field of IR and specifically the relevance of genetic algorithms to internet web search. Finally, from the proposals surveyed it turns out that GA is applied to diverse problem fields of internet web search.

Author(s):  
Zahid Ashraf Wani ◽  
Huma Shafiq

Nowadays, we all rely on cyberspace for our information needs. We make use of different types of search tools. Some of them have specialization in a specific format or two, while few can crawl a good portion of the web irrespective of formats. Therefore, it is very imperative for information professionals to have thorough understandings of these tools. As such, the chapter is an endeavor to delve deep and highlight various trends in online information retrieval from primitive to modern ones. The chapter also made an effort to envisage the future requirements and expectation keeping in view the ever-increasing dependence on diverse species of information retrieval tools.


Author(s):  
Roberto J.G. Unger ◽  
Isa Maria Freire

O artigo apresenta o conceito de regime de informação aos gestores de informação, como contribuição aos processos de adaptação e adequação de sistemas de informação e linguagens documentárias para atender às necessidades informacionais dos usuários. Regimes de informação são modos de produção informacional dominantes numa formação econômico-social que pressupõem, necessariamente, em seu contexto fontes de informação que são disseminadas e exercem influência no contexto social em que estão estabelecidas. Nesse aspecto, as sociedades têm regimes de informação através dos quais organizam a produção material e simbólica e representam a dinâmica das relações sociais. Dentre as diversas formas de manifestações institucionais atuais, destacam-se os sistemas de recuperação da informação, a manifestação per se do fenômeno que move o regime. Os sistemas de recuperação da informação, por sua vez, usam linguagens documentárias para organizar e comunicar a informação organizada nos inúmeros “agregados de informação”, que Barreto (1996) define como “estruturas” que armazenam “estoques de informação” e podem atuar como “agentes”, ou “mediadores”, entre uma fonte de informação e seus usuários. Abstract The article presents the concept of regime of information to information managers as a contribution for the proccesses of adaptation and adjustment of information systems and documentary language to really attend the information needs of users. Regimes of information are dominants modules of informational production in economic-social formation that presuppose, necessarily, in its context information sources wich are disseminated and put in actions influences in the structure which they are established. Under these circumstances, societies have regimes of information through whom organize symbolic and material production and represent the social dynamics relations. In the midst of several kinds of actual institutional manifestations, distinguish the information retrieval systems, the expression per se of the phenomenon that moves the regime. Under this configuration, the information retrieval systems make use of documentary language to organize, describe and communicate provided information in innumerable aggregates of information that, according Barreto (1996), “are structures which harvest “supply of information” and they operate as “agents” or “mediators” between a source of information and their users”.


Author(s):  
Bich-Liên Doan ◽  
Jean-Paul Sansonnet

This chapter discusses using context in Information Retrieval systems and Intelligent Assistant Agents in order to improve the performance of these systems. The notion of context is introduced and the state of the art in Contextual Information Retrieval is presented which illustrates various categories of contexts that can be taken into account when solving user queries. In this framework, the authors focus on the issue of task-based context which takes into account the current activity the user is involved in when he puts a query. Finally they introduce promising research directions that promote the use of Intelligent Assistant Agents capable of symbolic reasoning about users’ tasks for supporting the query process.


2018 ◽  
Vol 36 (3) ◽  
pp. 430-444
Author(s):  
Sholeh Arastoopoor

Purpose The degree to which a text is considered readable depends on the capability of the reader. This assumption puts different information retrieval systems at the risk of retrieving unreadable or hard-to-be-read yet relevant documents for their users. This paper aims to examine the potential use of concept-based readability measures along with classic measures for re-ranking search results in information retrieval systems, specifically in the Persian language. Design/methodology/approach Flesch–Dayani as a classic readability measure along with document scope (DS) and document cohesion (DC) as domain-specific measures have been applied for scoring the retrieved documents from Google (181 documents) and the RICeST database (215 documents) in the field of computer science and information technology (IT). The re-ranked result has been compared with the ranking of potential users regarding their readability. Findings The results show that there is a difference among subcategories of the computer science and IT field according to their readability and understandability. This study also shows that it is possible to develop a hybrid score based on DS and DC measures and, among all four applied scores in re-ranking the documents, the re-ranked list of documents based on the DSDC score shows correlation with re-ranking of the participants in both groups. Practical implications The findings of this study would foster a new option in re-ranking search results based on their difficulty for experts and non-experts in different fields. Originality/value The findings and the two-mode re-ranking model proposed in this paper along with its primary focus on domain-specific readability in the Persian language would help Web search engines and online databases in further refining the search results in pursuit of retrieving useful texts for users with differing expertise.


Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 449
Author(s):  
Amjad F. Alsuhaim ◽  
Aqil M. Azmi ◽  
Muhammad Hussain

Traditional information retrieval systems return a ranked list of results to a user’s query. This list is often long, and the user cannot explore all the results retrieved. It is also ineffective for a highly ambiguous language such as Arabic. The modern writing style of Arabic excludes the diacritical marking, without which Arabic words become ambiguous. For a search query, the user has to skim over the document to infer if the word has the same meaning they are after, which is a time-consuming task. It is hoped that clustering the retrieved documents will collate documents into clear and meaningful groups. In this paper, we use an enhanced k-means clustering algorithm, which yields a faster clustering time than the regular k-means. The algorithm uses the distance calculated from previous iterations to minimize the number of distance calculations. We propose a system to cluster Arabic search results using the enhanced k-means algorithm, labeling each cluster with the most frequent word in the cluster. This system will help Arabic web users identify each cluster’s topic and go directly to the required cluster. Experimentally, the enhanced k-means algorithm reduced the execution time by 60% for the stemmed dataset and 47% for the non-stemmed dataset when compared to the regular k-means, while slightly improving the purity.


Sign in / Sign up

Export Citation Format

Share Document