Information retrieval

more information available about a given topic, the more difficult it is to locate accurate and relevant information. Most users know what information they need, but are unsure where to find it. Search engines can facilitate the ability of the users to locate such relevant information. During the past few years, CBIR has gained much devotion for its potential application in multimedia management. The term ‘content’ in this context might refer to colors, shapes, texture, or any other information that

CHAPTER 1 INTRODUCTION Cloud storage system is a service model in which data are managed , maintained, and backuped remotely on the cloud side, and simultaneously keeps data available to the users over a network. Mobile Cloud Storage (MCS) [1], [2] represents a family of increasingly popular on-line services, and even is used as primary file storage for the mobile devices [3]. MCS helps the mobile device users to store and retrieve files or data on the cloud through wireless communication, which

word exists within a particular document, since it stores no information regarding the frequency and position of the word; it is therefore considered to be a Boolean index. Such an index determines which documents match a query but does not rank matched documents. In some designs the index includes additional information such as the frequency of each word in each document or the positions of a word in each document [1]. Position information enables the search algorithm to identify word proximity to

paper, the main focus will lie on the differences that the librarians and students have when they tend to retrieve or manage the information that they search through online databases. Furthermore, we will discuss the importance of the knowledge management and controlled vocabulary as the main distinction between those librarians who are successful at information retrieval and teaching it and those students that aren’t. We will discuss this under the light of some of the large search engines or web

ABSTRACT Scavenging information associated to particular person through search engines is one of the most common activities on the Internet. Result contains numbers of Web pages, which may be relevant to different person which includes queried name. Human languages are not correct. Text referring to the city "Roanoke" can mean "Roanoke, Virginia" or "Roanoke, Texas", depending on the surrounding context. Organizations and companies often have multiple nicknames, name variations, or common misspellings

research the Persian corpus, Hamshahri, is used for the experiments. It is collected in the database laboratory of the University of Tehran. This corpus is a standard collection that was used at CLEF for evaluation of Persian information retrieval systems. Also TREC (Text Retrieval Conference) standards are met in the formal version. The first version includes more than 166 thousand documents. They are collected from Hamshahri Newspaper website archive. They represent the general texts, spoken and written

21-May-2015 Complete List of Authors: Dan, Ovidiu; Lehigh University, Computer Science; Microsoft, Bing Davison, Brian; Lehigh University, Computer Science and Engineering Computing Classification Systems: Information Systems, Information Storage and Retrieval, Information Search and Retrieval Computing Surveys For Peer Review Department of Computer Science and Engineering College of Engineering and Applied Science 27 Memorial Drive West, Bethlehem, PA, 18015, USA Ovidiu Dan contact@ovidiudan.com

Professor, IIST-Rajpur 3Dept. of Computer Science Engineering, Rai University, Dholka 4Dept. of Information Techmology, V.Vnagar Abstract—The technique of Collaborative Filtering is especially successful in generating personalized recommendations. Collaborative Filtering is quickly becoming a popular technique for reducing information overload, often as a technique to complement content based information filtering. More than a decade of research has resulted in numerous algorithms, although no comparison

express data models which refers to objects and their relationships. These models are called RDF Models. Both XML and RDF deal with Metadata which is data about other data. Raw data is stored in some repository called as Database Storage. Then Information Extraction techniques like KM solutions generate metadata. But in

Abstract—Web searching engine are mostly used for finding certain information among a huge amount of data in a minimum amount of period. Profile based personalized web search (PWS) has determine their effectiveness in improving the quality of various internet search technique. We study security of privacy protection for PWS applications that as hierarchical user profiles. In this paper we can implement the PWS system called UPS that can flexibly create profiles by queries while regarding user definite