2013, Vol. 03, Issue. 03, pp. 10-17
ISSN 2012-9564 (Print)
ISSN 2012-9572 (Online)
© Author Names. Authors retain all rights.
IJCSRA has been granted the right to publish and share, Creative Commons 3.0
Application of Soft Computing In Information Retrieval - A
Review of Literature
Md. Nasar1, Md. Abu Kausar2, Sanjeev Kumar Singh3
School of computing Science and Engineering Galgotias University, Gr. Noida, India
Department of Computer and System Sciences, Jaipur National University, Jaipur, India
Department of Mathematics, Galgotias university, Gr. Noida, India
Information retrieval (IR) aims at defining systems able to provide a quick and efficient content based access to a huge amount of stored information. The goal of an IR system is to estimate the relevance of web documents to users' information needs, expressed by using a query. This is a extremely difficult and complex task, since it is pervaded with imprecision and uncertainty. Most of the existing IR systems offer a simple model of IR, which privileges efficiency at the expense of effectiveness. A promising direction to increase the effectiveness of IR is to model the concept of "partially intrinsic" in the
IR process and to make the systems adaptive, i.e. able to "learn" the user's concept of relevance. The application of soft computing techniques can be of assist to obtain greater flexibility in IR systems.
Keywords: Genetic Algorithm, Information retrieval, Differential Evolution, Neural Network, Ant Colony
Algorithm , Web Crawler.
Information retrieval dealt with the representation, storage, organization, and access to information items. The representation and association of the information items will provide the user with effortless access to the information in which he will be interested. Unfortunately, characterization of the client information need is not a simple problem. Find all the pages containing information on college cricket teams which are maintained by a university in the India and participate in the IPL tournament. To be relevant, the page must include information on the national ranking of the team in the last four years and the email or mobile number of the team coach. Clearly, this complete description of the player information need not be used directly to request information using the recent Web search engines. The user must first translate this information need into a query which will be processed by the IR system. In its most general form, this translation gives a set of keywords which summarize the description of the user information needed. Given the user query, the key goal of IR system is to retrieved information which may be relevant to the user. The detail about this is also discussed by (Md. Abu Kausar et al. 2013).
Now days it has become an important part of human life to use Internet to gain access the information from
WWW. The current population of the world is about 7.017 billion out of which 2.40 billion people (34.3%) use
Internet (see Figure 1). From .36 billion in 2000, the amount of Internet users has increased to 2.40 billion in
2012 i.e., an increase of 566.4% from 2000 to 2012. In Asia out of 3.92 billion people, 1.076 billion
(i.e.27.5%) use Internet, whereas in India out of 1.2 billion, .137 billion (11.4%) use Internet. Same growth rate is expected in near future too and it is not far away when anyone will start believing that the life is incomplete without Internet. Figure 1: illustrates Internet Users in the World Regions.
International Journal of Computer Science Research and Application, 3(3): 10-17
Figure 1: Internet Users in the World Regions (Source: www.internetworldstats.com accessed on 15-02-2013)
1.1 Information versus Data Retrieval
Data retrieval, in the context of an IR system, consists mostly of determining which