Dynamic User Profiles Research Articles

Towards a Ubiquitous User Model for Profile Sharing and Reuse

People interact with systems and applications through several devices and are willing to share information about preferences, interests and characteristics. Social networking profiles, data from advanced sensors attached to personal gadgets, and semantic web technologies such as FOAF and microformats are valuable sources of personal information that could provide a fair understanding of the user, but profile information is scattered over different user models. Some researchers in the ubiquitous user modeling community envision the need to share user model's information from heterogeneous sources. In this paper, we address the syntactic and semantic heterogeneity of user models in order to enable user modeling interoperability. We present a dynamic user profile structure based in Simple Knowledge Organization for the Web (SKOS) to provide knowledge representation for ubiquitous user model. We propose a two-tier matching strategy for concept schemas alignment to enable user modeling interoperability. Our proposal is proved in the application scenario of sharing and reusing data in order to deal with overweight and obesity.

Graph based Approach for Mining Frequent Sequential Access Patterns of Web pages

The Internet has impacted almost every aspect of our society. Since the number of web sites and web pages has grown rapidly, discovering and understanding web users’ surfing behavior are essential for the development of successful web monitoring and recommendation systems. To capture users’ web access behavior, one promising approach is web usage mining which discovers interesting and frequent user access patterns from web logs. Sequential Web page Access pattern mining has been a focused theme in data mining research for over a decade with wide range of applications. The aim of discovering frequent sequential access (usage) patterns in Web log data is to obtain information about the navigational behavior of the users. This can be used for advertising purposes, for creating dynamic user profiles etc. We propose a new approach for mining the web usage data by creating graph using web access sequence of sorted web log and mining the useful sequential access pattern.

Library Personalization Systems: an Indian experience

Personalization of library resources is projected as a viable alternative to tide over the information explosion and to conserve the time of users for more productive intellectual tasks. Personalization needs sufficient electronic content at one's site as well as suitable mechanisms to identify the user through his or her profile, selectively search the content that matches the user profile, and arrange and present it to the user in an appealing fashion. The different components of a content personalization system include: `Content Serving System' to host electronic content beyond a critical mass, `User Interest Management System' to manage dynamic user profiles, `Search Engine' to automatically match content with profiles and `Personalized Content Delivery' mechanisms for delivering matched results to the user. Technological advancements made by web enabled computing coupled with continued user interest to gather information resources available on the web led many popular portals to bring in the concept of content personalization suiting varied user interests. A few such initiatives are explained. Library personalization projects like MyLibrary in different university libraries in advanced countries are discussed. To explore the efficacy of library personalization systems in a developing country, the SAI personalization prototype developed in the Central Library of the Indian Institute of Technology, Kharagpur is described in detail.

MEMPHIS: A mobile agent-based system for enabling acquisition of multilingual content and providing flexible format internet premium services

Mobile Agent technology is an interesting concept for large network-based system structures. In this paper we describe a Java-based agent environment which integrates agent execution platforms into World Wide Web servers promoting a world wide infrastructure for Mobile Agents. This system has been developed within the framework of MEMPHIS IST project, which involves the definition, development and validation of a new system for commercially significant multilingual premium services, focused on thin clients such as mobile phones, Personal Digital Assistants, etc. The concept relies on the extraction of multilingual information from various web-based content sources in different formats. The system is composed by three different Modules, namely the Acquisition, the Transformation and the Distribution Module. The content acquisition is based on dynamic user profiles. The acquired content is transformed into a meta-representation, which enables content storage independent both of source and destination format and language. The output format is based on the requirements of employed thin client terminals and the output document is distributed via the appropriate networks. The end-user receives the required information as premium services via the chosen output medium. The system supports both pull and push services. An evaluation of the system is also presented.

웹 사용 정보 마이닝 기반의 동적 사용자 프로파일 생성

동적 웹 컨텐츠 제공에서 고객을 위한 추천서비스에 이르는 인터넷 기반의 전자상거래 애플리케이션에서는 고객이 어떤 성향을 가지고 있는가에 대한 정보를 획득하는 것이 중요하다. 웹 개인화의 대표적인 기술인 협력적 석과는 사용자의 정보를 정적인 프로파일 형태로 저장하여 사용자의 성향 변화를 빨리 획득할 수 없다. 또한 사용자의 명시적 평가 의존성, 확장성 부족, 다차원 공간 데이터에 대한 적용 어려움 둥의 문제점을 가지고 있다. 이와 같은 단점을 해결하기 위한 해결 방안으로 웹 사용 정보 마이닝(web usage mining)이 쓰이고 있다. 웹 사용 정보 마이닝은 서버에 축적된 웹 사용 데이터(web usage data)를 이용하여 패턴을 발견하는 기술이다. 특히 연관 규칙 생성 알고리즘으로 웹 사용 패턴(web usage pattern)을 찾고 패턴을 클러스터링하는 기술이 사용되고 있다. 그러나 연관 규칙 생성 알고리즘은 많은 수의 패턴들을 찾고 또 유용하지 못한 패턴을 발견하는 단점이 있다. 본 논문에서는 검증된 웹 사용 패턴을 이용한 동적 사용자 프로파일 생성 방법을 제안한다. 먼저 패턴 발견을 위해 연관 규칙 생성 알고리즘인 Apriori를 이용하고 사용자 프로파일을 위한 클러스터를 생성하기 위해 ARHP를 채택하였다. 클러스터를 생성하기 전에 Dempster-Shafer 이론을 이용하여 유용하지 못한 패턴을 제거하는 패턴 검증 과정을 수행한다. 검증된 패턴을 이용하여 클러스터를 생성하고 사용자의 현재 활성화된 세션에 따라 동적으로 사용자 프로파일이 생성된다 It is important that acquire information about if customer has some habit in electronic commerce application of internet base that led in recommendation service for customer in dynamic web contents supply. Collaborative filtering that has been used as a standard approach to Web personalization can not get rapidly user's preference change due to static user profiles and has shortcomings such as reliance on user ratings, lack of scalability, and poor performance in the high-dimensional data. In order to overcome this drawbacks, Web usage mining has been prevalent. Web usage mining is a technique that discovers patterns from We usage data logged to server. Specially. a technique that discovers Web usage patterns and clusters patterns is used. However, the discovery of patterns using Afriori algorithm creates many useless patterns. In this paper, the enhanced method for the construction of dynamic user profiles using validated Web usage patterns is proposed. First, to discover patterns Apriori is used and in order to create clusters for user profiles, ARHP algorithm is chosen. Before creating clusters using discovered patterns, validation that removes useless patterns by Dempster-Shafer theory is performed. And user profiles are created dynamically based on current user sessions for Web personalization.

Supporting global user profiles through trusted authorities

Personalization generally refers to making a Web site more responsive to the unique and individual needs of each user. We argue that for personalization to work effectively, detailed and interoperable user profiles should be globally available for authorized sites, and these profiles should dynamically reflect the changes in user interests.Creating user profiles from user click-stream data seems to be an effective way of generating detailed and dynamic user profiles. However a user profile generated in this way is available only on the computer where the user accesses his browser, and is inaccessable when the same user works on a different computer. On the other hand, the integration of Internet with telecommunication networks have made it possible for the users to connect to Web with a variety of mobile devices as well as desk tops. This requires that user profiles should be available to any desktop or mobile device on the Internet that users choose to work with.In this paper, we address these problems through the concept of "Trusted Authority". A user agent at the client side that captures the user click stream, dynamically generates a navigational history 'log' file in Extensible Markup Language (XML). This log files is then used to produce the 'user profiles' in Resource Description Framework (RDF). User's right to privacy is provided through the Platform for Privacy Preferences (P3P) standard. User profiles are uploaded to the trusted authority and served next time the user connects to the Web.The trusted authority concept, serving as a namespace qualifier, provides globally unique userid/password identification for users. Furthermore user profiles dynamically reflect the changes in their interests since the data generated while they are surfing the Web contribute to their profile. Also since the user profiles are defined in RDF, they are interoperable and available to any type of authorized device on the Internet.

Dynamic user profiles and flexible queries in office document retrieval systems

The problem of document management in an Office Information System in view of supporting the decision process by a set of users with different knowledge, capabilities and requirements is considered. User profiles are used to improve the retrieval properties and a control system is outlined to automatically update the utility information used by the searching strategies. user requirements are modeled in Dynamic User Profiles in order to maintain accurate knowledge of the most promising approach to document search, of the interest fields, and of the favourite output format. An example of DUP use is provided adopting a flexible query specification to take advantage of database selection, retrieval via keyword, or full text scanning in a multi-strategy query processing approach. Actual queries are redefined by extracting the aspects suitable for each strategy.