Information Retrieval on the World Wide Web

IAEME PUBLICATION, 2020

The searching of relevant content for any particular application area is a challenging task in today’s ocean of knowledge on the web. There are various factors such as user query, search technique and ranking algorithms that affect the traditional information retrieval process as well as the modern semantic based search systems. The present study aim to provide a comprehensive review of literature on the various approaches that are used for the retrieval and searching of the relevant e-content.

Communications in Computer and Information Science, 2011

The essential focus of Web Information Retrieval System (WIRS) is to address the parts of pursuit that consider the particular needs and objectives of the people conducting Web search. WIRS moves past the customary focus of robotized looking inside computerized accumulations, utilizing sagacious systems and Webbased innovations to help clients in tagging their data needs, evaluating and investigating query items, and dealing with the information they discover. The objective of this paper is to give an outline of the key issues, challenges, and opportunities in WIRS research.

Information Retrieval is the activity of obtaining information resources relevant to an information need from a collection of information resources. A web search engine is a software system that is designed for the purpose of information retrieval on the World Wide Web. The search results are generally presented in a line of results often referred to as search engine results pages. In today's age, where the amount of information available on the Internet is millions of Gigabytes, it becomes highly necessary to implement efficient search techniques in order to index and rank such massive amounts of data. This paper provides the user with a great search experience and helps to get the relevant search results with minimal memory consumption. It has the following parts-The crawler which crawls the different websites and stores the crawled data, indexing module which helps to find information relating to the query as quickly as possible, the process of lemmatization for grouping together the different infected forms of a word as a single item and a ranking module that ranks the results so as to provide the " best" results. This work when tested as a desktop application, for different search queries, provides satisfactory outcomes in regards to the relevancy of the results to the entered query and also efficient in terms of memory consumption. It has been observed that the average indexing time for a document is around 1 second. Also, for a typical search query with 3 terms, on an average, the memory consumption is around 200 MB and the execution time is around 5 seconds.

Computing in Science and Engineering, 2004

The first Web information services were based on traditional information retrieval algorithms, which were originally developed for smaller, more coherent collections than the Web. Due to the Web's continued growth, today's Web searches require new techniquesexploiting or extending linkages among Web pages, for example.

2003

In this paper we briefly explore the challenges to expand information retrieval (IR) on the Web, in particular other types of data, Web mining and issues related to crawling. We also mention the main relations of IR and soft computing and how these techniques address these challenges.

1997

With the explosive growth of the Web, one of the biggest challenges in exploiting the wealth of available information is to locate the relevant documents. Search engines play a crucial role in addressing this problem by precompiling a large index of available information to quickly produce a set of possibly relevant documents in response to a query. While most Web users make extensive use of the Internet search engines, few people have more than a vague idea of how these systems work.

Web Semantics: Science, Services and Agents on the World Wide Web, 2012

More and more (semi) structured information is becoming available on the web in the form of documents embedding metadata (e.g., RDF, RDFa, Microformats and others). There are already hundreds of millions of such documents accessible and their number is growing rapidly. This calls for large scale systems providing effective means of searching and retrieving this semi-structured information with the ultimate goal of making it exploitable by humans and machines alike.

Many information resources available over the Internet only provide browsing and pre-defined navigation capabilities. If the user is interested in simple word matches on documents as a whole, search engines such as Yahoo or AltaVista may be adequate. For resources of high volume, the user should be able to specify preferences and just obtain the relevant portions of a resource. In this paper, we study the problem of enhancing the search capability to an existing resource by implementing and evaluating two approaches: use of (i) structured (relational) database or, (ii) HTML documents enhanced with meta tags.

2008

Searching for information is commonly an individual task which aims at solving any information need. To do that, one may go to a library, or go surfing the Web in order to find relevant information. Indeed, due to the large amount of available documents, the Web has become a favorite information source for solving daily information needs. An issue remains: the Web is in perpetual evolution; so the problem is less the existence of relevant information rather than the way users find it. One may compare searching for information on the Web with "looking for a needle in a haystack." Thus, searching the Web suffers from many limits that can be reduced by using a search assistant. Such an assistant helps the user to find relevant information on the Web. At the beginning, those assistants were principally helping each user individually. Nowadays, we are witnessing the rise of social approaches in such systems. Those latter systems help users to find relevant information by using other users' experience, shared information… Therefore, each user is helped thanks to the mass crowd. This chapter underlines this search assistants evolution, it is organized as follows: section 1 introduces the underlying concepts and limits of traditional information search process and its application to the Web. Section 2 explains the search assistant concept by detailing their evolution from individual to social approaches. Sections 3 up to 5 present current approaches that search assistants may use to help any user to query and browse the Web as well as to improve search-related activities. To conclude, future trends for Web information assistants are discussed.

World wide web (WWW), also known as web has become one of the most valuable resources of Information Retrieval (IR) and Knowledge Discovery. Due to the increasing amount of data available on the Internet, the effective information retrieval requires an efficient framework that can provide a communication between clients as well as for servers. Information Retrieval involves the searching and retrieval of knowledge from large database collections. In this paper, the analysis and comparison of the IR techniques is done. The analysis is based on the Information Retrieval in distributed environments, grid and the cloud environments. Different crawling techniques in these environments are also discussed in this paper.