Information retrieval

section describes different semantic methodologies being forwarded by the scholars. Currently, various types of search engines are being deployed to access the information required. Each search engine has its own features and uses different algorithms to index, rank and present web documents. Hence the result put forth on information retrieval by the search engines are different from one another. And there is not a definite and unique single technology or architecture that leads to a logical and meaningful

approach was introduced in [11], which mainly focuses on finding information about physical objects. An image-based QA system allows direct use of an image that refers to the object. This type of systems was designed to find multimedia answers from web-scale media resources such as Flicker, Google images. D. Multimedia QA Search: Due to the increasing amount of digital information stored over the web, searching for desired information has become an essential task. The research in this area started

INTRODUCTION 1.1 GENERAL The wide adoption of the Internet has fundamentally altered the ways in which user communicate, gather information, conduct businesses and make purchases. As the use of World Wide Web is increasing, data on internet is increasing. A few sites consist of millions of pages, but millions of sites only contain a handful of pages. Few sites contain millions of links, but many sites have one or two. Millions of users flock to a few select sites, giving little attention to millions

as image based output on the type of query provided by the user. The input can also be text based or image based. The results obtained are re-ranked and prioritized according to user intention and also differ with respect to different users. The information of users search interests are stored offline and a profile based system is maintained for each and every user so that accurate results are obtained for different users working on the same device. Keywords— Smartphone image recommender, image recommender

and recognition. Dataset Splitter The Dataset stacking stage is the procedure in charge of dividing the dataset into two sections got from the preprocessing module. Holdout system is utilized to part the dataset into two sections where given information are

approach of how they seek knowledge: From hours, and hours of researching in the library to find information, to a five-second research on the internet with a click of a button? In an ever-changing world, humans are evolving with the ease of technology. The google search engine allows the users to search anything with the tip of their fingers. The World Wide Web has billions of website with information. People can search anything they want to know about. The innovation of the Google search engine

Search is a platform offered by Google that allows web developers to offer customized information in web search results. Also, classified and organize the queries and create customized search engines based on Google search [7-8]. Google Search API is used to provide keywords for search engine Google and get the retrieval results from Google, and the combination of these two things can help users to find the information needed to better search [9]. The method consists of

contain more information on various entities described in the document. In this report, we have surveyed well known research papers in the field of named entity disambiguation and have described the approaches suggested in them. Successive sections of report aim to solve the shortcomings of the algorithms discussed in the previous sections.   INTRODUCTION The recent years have seen a huge increase in the number of online documents. This has resulted in a huge amount of information being available

Answering system. My master’s thesis is an extension to this study, for which, I am working with “Morpheus” team at Database Research Center in our department. Our team is building a question answering system that uses deep web sources by exploiting information from Wikipedia and WordNet along with sample query answering strategies provided by users. The motivation behind this research work is as follows. If we search for an answer to a question in a typical search engines such as Google, Bing, or Yahoo

Background Summary Founded on September 4, 1998 Google quickly revolutionized the search engine and the Internet alike. Within two years of starting operations Google had become the largest single search engine in the world and began to dominate the market. As the World Wide Web (web) grew in popularity and became more and more a part of everyone’s daily life, Google too grew in popularity “because it could provide simple, fast, and relevant search results” (Deresky, 2011). The differentiating