52 Slices
Medium 9781601322517

An adaptive navigation support based on a new technology

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, Joan Lu, George Jandieri, Ashu M. G. Solo, Fernando G. Tinetti CSREA Press PDF

Int'l Conf. Information and Knowledge Engineering | IKE'13 |

181

An adaptive navigation support based on a new technology

Rim Zghal Rebaî, Corinne Amel Zayani and Ikram Amous

MIRACL

ISIMS, El Ons City, Sfax University, Tunis Road Km 10, Sakiet Ezzit 3021 Sfax, Tunisia rim_zghal@yahoo.fr, zayani@irit.fr, ikram.amous@isecs.rnu.tn

Abstract— In the current information systems and especially in the case of a large amount of data, the user can be easily disoriented and cannot get the required information. Several methods are proposed to support the user along his navigation.

All these methods are applied only on simple links by taking into account a set of parameters related to the user, the context, etc.

In this paper we propose an adaptive navigation method which allows (i) to identify the best navigation path between semistructured result documents by taking into account the user’s history, needs and device’s characteristics, (ii) to apply on both simple and extended links the adaptive navigation technologies and (iii) to reduce the navigation space by using a new adaptive navigation technology “Extended XLINK technology” which is based on the basic idea of the XLINK extended links.

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Medium 9781601322517

A Method for Vr Management in Public Opnion

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, Joan Lu, George Jandieri, Ashu M. G. Solo, Fernando G. Tinetti CSREA Press PDF

Int'l Conf. Information and Knowledge Engineering | IKE'13 |

247

A METHOD FOR VR MANAGEMENT

IN PUBLIC OPINION

Jin Du, Yanhui Du

Chinese People’s Public Security University, Beijing koaladj@126.com, dyh6889@126.com

Abstract

Public opinion management system plays an important role on information management nowadays. Developing characteristics and rules of online public opinion are discussed by means of optimized model analyzing method in present paper. The public opinion was regarded as a

‘resource’ from which the conception of

‘configuration’ was proposed and its control model was developed as well. Based on that, correlation degree variables between ‘social network’ cluster nodes were dynamically introduced and general rules of public opinion between associated network cluster management were studied at the time. The

‘public opinion resource’ correlation optimized model which can regulate the relationship between

VR management and verified by means of empirical research of sociology, journalism and psychology. At last, artificial intelligence and decision support can be supplied to relevant industries by instructing system design and management system by means of the study of public opinion.

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Medium 9781601322517

On-line Weighted Matrix Factorization for TV Program Recommendation

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, Joan Lu, George Jandieri, Ashu M. G. Solo, Fernando G. Tinetti CSREA Press PDF

Int'l Conf. Information and Knowledge Engineering | IKE'13 |

207

On-line Weighted Matrix Factorization for TV Program

Recommendation

Jin Jeon1 and Munchurl Kim2

Department of Electrical Engineering, Korea Advanced Institute of Science and Technology,

Yuseong-gu, Daejeon, Korea

1, 2

Keywords: Matrix Factorization, Collaborative Filtering, TV

Personalization

1

Introduction

As massive amounts of information for contents are available at users’ sides, recommender systems have become popular to enhance user experience. The MF is known as an effective collaborative filtering which analyzes relationships between users and items. The MF models map both users and items to a joint latent factor vector in a multi-dimensional space as inner products of user-item interactions [1]. The MF models are based on the rating values which are not usually available in TV domain. Instead, the user watching history of

TV programs can be used for TV recommender systems [2].

In TV domain, TV programs are often provided as TV program series such as News, Shows, Dramas, Sports etc. In this case, such individual TV programs cannot be dealt as different items such as movie items. Instead, the TV programs in the same series must be treated as single TV program titles in MF. The time-varying trend of user preference on TV programs must also be taken into account in MF [3]. In this paper, we consider these three facts in MF for TV program recommender systems.

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Medium 9781601322517

Using Graph Theoretic Approach to Digital Steganography

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, Joan Lu, George Jandieri, Ashu M. G. Solo, Fernando G. Tinetti CSREA Press PDF

270

Int'l Conf. Information and Knowledge Engineering | IKE'13 |

Using Graph Theoretic Approach to Digital Steganography

Nasreddin Bashir El Zoghbi

P.G.V.Suresh Kumar

Dean, Dept. o f Computer Science & I.T

Tripoli University

Tripoli, Libya nzoghobi@yahoo.com

Dept. of Co mputer Science & I.T

Adama Sci&Tec Un iversity

Adama, Ethiopia pendemsuresh@gmail.co m

Getahun Mekuria

Deputy Scientific Director

Addis Ababa Institute of Technology

Addis Ababa, Ethiopia getahun4433@g mail.co m

Abstract— Steganography literally means secret writing.

The technique has been used in various forms for 2500 years or long. It has found its application in various fields including military, diplomatic, personal and intellectual property applications. Briefly stated, Steganography is the term applied to any number of processes that will hide a message within an object, where the hidden message will not be apparent to an observer. The paper describes the concept of finding natural relationship between a digital cover and a message. The relationship can be used to hide the information in cover without actually replacing or distorting any useful bits of the cover. It introduces a concept called sustainable embedding of message in a cover using natural relationship and representing it using graph theoretic approach.

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Medium 9781601322517

A System for Keyword Search on Probability XML Data

Hamid R. Arabnia, Leonidas Deligiannidis, Ray Hashemi, Joan Lu, George Jandieri, Ashu M. G. Solo, Fernando G. Tinetti CSREA Press PDF

Int'l Conf. Information and Knowledge Engineering | IKE'13 |

61

A System for Keyword Search on Probability XML Data

Weidong Yang1 , Hao Zhu1 , Zheng Zheng1 , Huirong Chen2 , Lei Wang2

1 Computer School, Fudan University, Shanghai, China

2 Commercial Aircraft Corporation of China, Ltd, Shanghai, China

Abstract— Many probabilistic XML data models have been proposed to store XML data with uncertainty information, and based on them the issues such as structured querying are extensively studied. As an alternative to structured querying, keyword search in probabilistic XML data needs to be concerned. In this paper we addressed the issue of keyword search on probabilistic XML data. The probabilistic XML data is viewed as a labeled tree, and a concept of Minimum

Meaningful Fragment (MMF) is defined as the searching result. A MMF is a minimum subtree of the probabilistic

XML data which has a positive probability of containing all keywords. To sort the MMFs a novel scoring function mainly considering the degree of uncertainty information is presented. We propose a system to compute top-k searching results efficiently based on the scoring function. The experiments shows the efficiency for our system.

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