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Online searching of books have gained astounding popularity worldwide. It has also attracted variety of researchers globally. Searching of books (e.g. Amazon.com, aNobii, LibraryThing etc) with the help of Social metadata(e.g. tags, reviews) and professional metadata (e.g. ISBN Number, Title, Publisher) is gradually becoming a sizzling hot topic under the aegis of Information Retrieval. In this paper,...
True Muslims around the world believe in Al Quran and Hadith. Al Quran is the principal religious text of Islam, a revelation from Allah. Hadith is also one of the fundamental sources of Islamic references and guidance for the Muslims after the Holy Book, Al-Quran. Hadith is referred to a report, statement, act, story, narration or discourse. Hadith, originally in Arabic, covers a wide range of issues...
new notion called statistics privacy, i.e., the property that predicate privacy is preserved even when the statistical distribution of keywords is known. The second scheme we proposed makes a tradeoff between statistics privacy and storage efficiency (of the delegate). Compared to PEKS, both schemes introduce reasonable
In a real world, it is often in a group setting that sensitive information has to be stored in databases of a server. Although personal information does not need to be stored in a server, the secret information shared by group members is likely to be stored there. The shared sensitive information requires more security and privacy protection. To our best knowledge, there is no paper which deals with...
isowned by multi persons. In this approach, we haveproposed a new scheme to deal with preserving the privacyin encrypted cloud data using multi-keyword searching. Toenable cloud server to perform access securely to searchingthe data with no cognizance about the real data of bothkeywords and trapdoors.
The authors present some experiments that show the capabilities of using recurrent neural networks (RNNs) in conjunction with hidden Markov models (HMMs) in the context of keyword spotting (KWS): the automatic recognition of a small set of keywords as they occur in unconstrained speech and/or noise. KWS is usually
automated free text evaluation system(s) using keyword and associated expression based technique. The proposed method uses human evaluated answers as training data and using Rough Set Theory, extracts information from them to be used in the shortlisting and weighing of keywords which are to be used in assessment. The results
reuse repository for software under development. In this paper we have discussed various search techniques for efficient retrieval of components from reuse repository. The paper highlights the concept of keyword-based search technique in a lucid manner by exemplifying the working procedure of the technique via its
In this paper, we present a keyword extraction methodology from handwritten Chinese document image based on matching and voting of the local topological structure. In the process, a handwritten keyword image is used as template, from which the local topological structure features of each character pixel are extracted
This paper presents a keyword spotting system based on the NSHP-HMM. This model allows to dynamically create global word models from letters models, and do not require any writing segmentation. The second section describes our system and its application to a keyword-based handwritten mail sorting task. Next section
This paper describes a mechanism of defining keywords on our Information Utilization System, which we have proposed to utilize information received via e-mail. Our system utilizes metadata of e-mail messages to organize pieces of information, and keywords are used to classify pieces of information based on their
A user stores his personal files in a cloud, and retrieves them wherever and whenever he wants. For the sake of protecting the user data privacy and the user queries privacy, a user should store his personal files in an encrypted form in a cloud, and then sends queries in the form of encrypted keywords. However, a
A solution of a keyword query over graphs is a Group Steiner tree, which is rooted at a node and whose nodes collectively satisfy the query (e.g. node keywords cover all the query keywords), and in which the sum of edge weights satisfies given conditions (e.g., need to be minimum or be the first K minimal among all
The paper proposes an ID-based encryption with keyword search scheme from bilinear pairings(IDEKS).It enables one user to send a secret key Tw derived from the receiver's identity to a server-a mail server and private key generator (MPKG) that will enable the server locate all encrypted messages containing
There are a number of searchable encryption schemes that allow secure conjunctive keyword searches over encrypted data, but all of them assume that the position of the keywords is known. This is a pity, since in unstructured text, e.g. the body of an e-mail, this position is unknown and one has to construct O
Keyword extraction aims to find representative phrases for a document. Graph-based keyword extraction represent the input document as a graph and rank its nodes according to their score using graph-based ranking method. In this paper, we propose a method to compute importance of co-occurrence word in document and
One of the most convenient ways to query XML data is a keyword search because it does not require any knowledge about XML structure and without the need to learn a new user interface. However, keyword search interface is very flexible. It is hard for a system to decide which node is likely to be chosen as a return
Spatial keyword querying has attracted considerable research efforts in the past few years. A prototypical query takes a location and keywords as arguments and returns the k objects that score the highest according to a ranking function. While different scoring functions have been used, how to compare different
Recently, a great deal of attention has been focusing on processing keyword search over static and XML streams. Keyword search is becoming more popular for its simplicity and its user-friendliness in querying XML databases. However, it is hard to express real search intention with just keyword search. There are many
propose Term-Frequency and Inverse Document Frequency (TF-IDF) method to rank keywords of top twenty most followed Instagram users based on image captions of Instagram. The objective of this research is to automatically know the main idea of Instagram users based on 50 recent image captions posted. In our experiments, TF-IDF
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