Infomarker—A New Internet Information Service System

As the web grows,the massive increase in information is placing severe burdens on information retrieval and sharing.Automated search engines and directories with small editorial staff are unable to keep up with the increasing submission of web sites.To address the problem,this paper presents Infomarker-an Internet information service system based on open Directory and Zero-Keyword Inquiry,The Open DIrectory sets up a net-community in which the increasing netcitizens can each organize a small portion of the web and present it to the others.By means of Zero-Keyword Inquiry,user can get the information he is interested in with out inputting any keyword that is often required by search engines,In Infomarker,user can record the web address he likes and can put forward an information request based on his wed records.The information matching engine checks the information in the Open Directory to find what fits user‘s needs and adds it to user‘s web address records.The key to the matching process is layered keyword mapping.Informarker provides people with a whole new approach to getting information and shows a wide prospect.     

利用Bookmark服务进行网络信息过滤

信息过滤(information filtering)是解决网络信息查询困难的重要方法,其核心技术是用户信息需求的获取和信息匹配算法.该文从这两方面讨论了在Internet上进行信息过滤的问题.在用户信息获取方面,提出通过扩展浏览器上的Bookmark功能,跟踪用户信息需求,并直接利用用户评价文章来表达用户需求.在信息匹配方面,提出最大间距进行ranking的算法.实验表明,它比传统算法精度更高.作为对上述方法的实现,设计了Bookmark服务系统,给出其系统框图,并介绍了它的功能.     

Organizing domain-specific information on the Web: An experiment on the Spanish business Web directory

Web directories organize voluminous information into hierarchical structures, helping users to quickly locate relevant information and to support decision-making. The development of existing ontologies and Web directories either relies on expert participation that may not be available or uses automatic approaches that lack precision. As more users access the Web in their native languages, better approaches to organizing and developing non-English Web directories are needed. In this paper, we have proposed a semi-automatic framework, which consists of anchor directory boosting, meta-searching, and heuristic filtering, to construct domain-specific Web directories. Using the framework, we have built a Web directory in the Spanish business (SBiz) domain. Experimental results show that the SBiz Web directory achieved significantly better recall, F-value, efficiency, and satisfaction rating than the benchmark directory. Subjects provided favorable comments on the SBiz Web directory. This research thus contributes to developing a useful framework for organizing domain-specific information on the Web and to providing empirical findings and useful insights for end-users, system developers, and researchers of Web information seeking and knowledge management.     

基于多变量Probit回归的用户兴趣挖掘方法

用户兴趣挖掘一直是很多领域的基础问题,例如推荐系统、个性化检索和在线广告。一个用户在Internet或现实生活中的历史行为虽然能反映用户的兴趣,但是如果用户第一次使用网络,因为缺少历史行为信息,系统很难获得用户的兴趣。为解决无法获取新用户兴趣的问题,本文提出一种基于多变量Probit回归的用户兴趣挖掘方法。采用马尔科夫链蒙特卡洛(MCMC)方法估计模型的后验分布。通过合成数据与豆瓣明星对电影的兴趣验证模型的性能,结果表明所提出的方法能够有效地预测冷启动用户的兴趣。     

SWI: A Semantic Web Interactive Gazetteer to support Linked Open Data

Current implementations of gazetteers, geographic directories that associate place names to geographic coordinates, cannot use semantics to answer complex queries (most gazetteers are just thesauri of place names), use domain ontologies for place name disambiguation, make their data sets available in the Semantic Web or support the use of Volunteered Geographic Information (VGI). A new generation of gazetteers has to tackle these problems. In this paper, we present a new architecture for gazetteers that uses VGI and Semantic Web tools, such as ontologies and Linked Open Data to overcome these limitations. We also present a gazetteer, the Semantic Web Interactive Gazetteer (SWI), implemented using this architecture, and show that it can be used to add absent geographic coordinates to biodiversity records. In our tests, we use this gazetteer to correct geographic data from a big sample (around 142,000 occurrence records of Amazonian specimens) from SpeciesLink, a big repository of biodiversity collection records from Brazil. The tests showed that the SWI Gazetteer was able to add geographic coordinates to around 30,000 records, increasing the records with coordinates from 30.29% to 57.5% of the total number of records in the sample (representing an increase of 90%).     

A metagenetic algorithm for information filtering and collection from the World Wide Web

This paper describes the implementation of evolutionary techniques for information filtering and collection from the World Wide Web. We consider the problem of building intelligent agents to facilitate a person's search for information on the Web. An intelligent agent has been developed that uses a metagenetic algorithm in order to collect and recommend Web pages that will be interesting to the user. The user's feedback on the agent's recommendations drives the learning process to adapt the user's profile with his/her interests. The software agent utilizes the metagenetic algorithm to explore the search space of user interests. Experimental results are presented in order to demonstrate the suitability of the metagenetic algorithm's approach on the Web.     

Cognitive styles and users’ responses to structured information representation

Structured information repositories, such as digital libraries, Web directories, and subject gateways, require effective ways to organise and manage information. This paper focuses on Web directories and investigates the relationships between users cognitive styles and information representation. The results indicate that cognitive style influences participants reactions to the organisation of subject categories, presentation of the results, and screen layout. The findings are applied to develop a design framework that can support the improvement of Web directories and other structured digital information resources. Finally, implications for information representation are discussed.     

User profiling for Web page filtering

To help address pressing problems with information overload, researchers have developed personal agents to provide assistance to users in navigating the Web. To provide suggestions, such agents rely on user profiles representing interests and preferences, which makes acquiring and modeling interest categories a critical component in their design. Existing profiling approaches have only partially tackled the characteristics that distinguish user profiling from related tasks. The authors' technique generates readable user profiles that accurately capture interests, starting from observations of user behavior on the Web.     

Modeling user interests by conceptual clustering

As more information becomes available on the Web, there has been a crescent interest in effective personalization techniques. Personal agents providing assistance based on the content of Web documents and the user interests emerged as a viable alternative to this problem. Provided that these agents rely on having knowledge about users contained into user profiles, i.e., models of user preferences and interests gathered by observation of user behavior, the capacity of acquiring and modeling user interest categories has become a critical component in personal agent design. User profiles have to summarize categories corresponding to diverse user information interests at different levels of abstraction in order to allow agents to decide on the relevance of new pieces of information. In accomplishing this goal, document clustering offers the advantage that an a priori knowledge of categories is not needed, therefore the categorization is completely unsupervised. In this paper we present a document clustering algorithm, named WebDCC (Web Document Conceptual Clustering), that carries out incremental, unsupervised concept learning over Web documents in order to acquire user profiles. Unlike most user profiling approaches, this algorithm offers comprehensible clustering solutions that can be easily interpreted and explored by both users and other agents. By extracting semantics from Web pages, this algorithm also produces intermediate results that can be finally integrated in a machine-understandable format such as an ontology. Empirical results of using this algorithm in the context of an intelligent Web search agent proved it can reach high levels of accuracy in suggesting Web pages.     

Research interests: their dynamics,structures and applications in unifying search and reasoning

Most scientific publication information, which may reflects scientists’ research interests, is publicly available on the Web. Understanding the characteristics of research interests from previous publications may help to provide better services for scientists in the Web age. In this paper, we introduce some parameters to track the evolution process of research interests, we analyze their structural and dynamic characteristics. According to the observed characteristics of research interests, under the framework of unifying search and reasoning (ReaSearch), we propose interests-based unification of search and reasoning (I-ReaSearch). Under the proposed I-ReaSearch method, we illustrate how research interests can be used to improve literature search on the Web. According to the relationship between an author’s own interests and his/her co-authors interests, social group interests are also used to refine the literature search process. Evaluation from both the user satisfaction and the scalability point of view show that the proposed I-ReaSearch method provides a user centered and practical way to problem solving on the Web. The efforts provide some hints and various methods to support personalized search, and can be considered as a step forward user centric knowledge retrieval on the Web. From the standpoint of the Active Media Technology (AMT) on the Wisdom Web, in this paper, the study on the characteristics of research interests is based on complex networks and human dynamics, which can be considered as an effort towards utilizing information physics to discover and explain the phenomena related to research interests of scientists. The application of research interests aims at providing scientific researchers best means and best ends in an active way for literature search on the Web.     

基于主体的语义Web服务自动组合研究

语义Web服务要解决的一个主要问题就是如何实现服务组合自动化.主体技术因其智能性、自主性等特点在解决语义Web服务组合问题中具有较大优势.通过分析语义Web服务组合研究现状,分析主体、语义Web与Web服务的紧密关系,论证了基于主体的语义Web服务的可行性并描述了基于多主体的Web服务组合平台架构.介绍了基于主体技术的语义Web服务组合技术,将服务组合看成是一个多主体环境下的规划问题,给出语义Web服务作为主体动作子类的形式化定义,并针对服务组合问题增加限定条件,定义服务之间的5种关系,试图从逻辑角度,以描述逻辑为基本工具,突出服务的动态性与交互性.最后利用主体的目标规划以及基于描述逻辑的有效推理,给出了服务的自动组合算法.     

Building Web Knowledge Flows based on Interactive Computing with Semantics

Web personalized services alleviate the burden of information overload by providing right information which meets individual user’s needs. How to obtain and represent knowledge needed by users is a key issue. This paper presents Web Knowledge Flow (WKF) to represent the specific knowledge on Web pages and a model of Interactive Computing with Semantics (ICS) to provide a feasible means of generating WKF. Objective WKF (OWKF) and Real-time WKF (RWKF) are firstly proposed to satisfy staged and real-time user interests. Secondly, the generation algorithm of WKF is proposed based on Semantics Link Network. Thirdly, “interactive point” is introduced to detect the moment of user interests change to ensures the dynamics of WKF. Experimental results demonstrate that ICS can effectively capture the change of user interests and the generated WKF can satisfy user requirements accurately.     

Unifying and targeting cultural activities via events modelling and profiling

Today, people have only limited, valuable spare time at their hands which they want to fill in as good as possible according to their interests. At the same time, cultural institutions are trying to attract interested communities to their carefully planned cultural programs. To distribute these cultural events to the right people, we developed a framework that will aggregate, enrich, recommend and distribute these events as targeted as possible. The aggregated events are published as Linked Open Data using an RDF/OWL representation of the EventsML-G2 standard. These event items are categorised and enriched via smart indexing and linked open datasets available on the Web of data. For recommending the events to the end-user, a global profile of the end-user is automatically constructed by aggregating his profile information from all user communities the user trusts and is registered to. This way, the recommendations take profile information into account from different communities, which has a detrimental effect on the recommendations. As such, the ultimate goal is to provide an open, user-friendly recommendation platform that harnesses the end-user with a tool to access useful event information that goes beyond basic information retrieval. At the same time, we provide the (inter)national cultural community with standardised mechanisms to describe/distribute event and profile information.     

A SUPER‐AGENT‐BASED FRAMEWORK FOR REPUTATION MANAGEMENT AND COMMUNITY FORMATION IN DECENTRALIZED SYSTEMS

In this article, we propose a novel super‐agent‐based framework for reputation management and community formation in decentralized systems. We describe this framework in the context of Web service selection where agents with more capabilities act as super‐agents. These super‐agents serve as reputation managers to maintain reputation information of services and share the information with other consumer agents that have fewer capabilities than the super‐agents. In addition, super‐agents can maintain communities and build community‐based reputation for a service based on the opinions from all community members that have similar interests and judgement criteria as the super‐agents or the other community members. A practical reward mechanism is also introduced to create incentives for super‐agents to contribute their resources (to maintain reputation and form communities) and provide truthful reputation information. Experimental results obtained through simulation confirm that our approach achieves better effectiveness and scalability compared to the systems that do not use super‐agents and that do not form communities.     

Open annotations on multimedia Web resources

Many Web portals allow users to associate additional information with existing multimedia resources such as images, audio, and video. However, these portals are usually closed systems and user-generated annotations are almost always kept locked up and remain inaccessible to the Web of Data. We believe that an important step to take is the integration of multimedia annotations and the Linked Data principles. We present the current state of the Open Annotation Model, explain our design rationale, and describe how the model can represent user annotations on multimedia Web resources. Applying this model in Web portals and devices, which support user annotations, should allow clients to easily publish and consume, thus exchange annotations on multimedia Web resources via common Web standards.     

Toward an agent-based and context-oriented approach for Web services composition

This paper presents an agent-based and context-oriented approach that supports the composition of Web services. A Web service is an accessible application that other applications and humans can discover and invoke to satisfy multiple needs. To reduce the complexity featuring the composition of Web services, two concepts are put forward, namely, software agent and context. A software agent is an autonomous entity that acts on behalf of users and the context is any relevant information that characterizes a situation. During the composition process, software agents engage in conversations with their peers to agree on the Web services that participate in this process. Conversations between agents take into account the execution context of the Web services. The security of the computing resources on which the Web services are executed constitutes another core component of the agent-based and context-oriented approach presented in this paper.     

A text mining approach on automatic generation of web directories and hierarchies

The World Wide Web (WWW) has been recognized as the ultimate and unique source of information for information retrieval and knowledge discovery communities. Tremendous amount of knowledge are recorded using various types of media, producing enormous amount of web pages in the WWW. Retrieval of required information from the WWW is thus an arduous task. Different schemes for retrieving web pages have been used by the WWW community. One of the most widely used scheme is to traverse predefined web directories to reach a user's goal. These web directories are compiled or classified folders of web pages and are usually organized into hierarchical structures. The classification of web pages into proper directories and the organization of directory hierarchies are generally performed by human experts. In this work, we provide a corpus-based method that applies a kind of text mining techniques on a corpus of web pages to automatically create web directories and organize them into hierarchies. The method is based on the self-organizing map learning algorithm and requires no human intervention during the construction of web directories and hierarchies. The experiments show that our method can produce comprehensible and reasonable web directories and hierarchies.     

Amalthaea: An Evolving Multi-Agent Information Filtering and Discovery System for the WWW

Amalthaea is an evolving, multi-agent ecosystem for personalized filtering, discovery, and monitoring of information sites. Amalthaea's primary application domain is the World Wide Web and its main purpose is to assist its users in finding interesting information. Two different categories of agents are introduced in the system: filtering agents that model and monitor the interests of the user and discovery agents that model the information sources.A market-like ecosystem where the agents evolve, compete, and collaborate is presented: agents that are useful to the user or other agents reproduce, while low-performing agents are destroyed. Results from various experiments with different system configurations and varying ratios of user interests versus agents in the system are presented. Finally issues like fine-tuning the initial parameters of the system and establishing and maintaining equilibria in the ecosystem are discussed.