web

Abstract: This chapter discusses content-based recommendation systems, i.e., systems that recommend an item to a user based upon a description of the item and a profile of the user’s interests. Content-based recommendation systems may be used in a variety of domains ranging from recommending web pages, news articles, restaurants, television programs, and items for sale. Although the details of various systems differ, content-based recommendation systems share in common a means for describing the items that may be recommended, a means for creating a profile of the user that describes the types of items the user likes, and a means of comparing items to the user profile to determine what to re commend. The profile is often created and updated automatically in response to feedback on the desirability of items that have been presented to the user.

 recommendations;  web;  

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Abstract: We propose a novel method to support analytical processes by visually integrating context information directly into web pages. The context information is obtained from knowledge bases or services that provide additional information about certain concepts and instances of a knowledge domain. The approach performs implicit queries on the underlying information sources using the key phrases of the web page and visually presents the results to the user in a seamless way. The technique aims at improving the integration of different information sources into the users task. The method has two phases, an augmentation and an interaction phase. In the augmentation phase, for each key phrase the availability of additional context information is checked. All phrases for which context information is available are highlighted by adding special markups and scripts to the web page. In the interaction phase, the user can click on a highlighted phrase to receive the associated context information. The information is displayed directly in the web page in an overlay that we call a semantic lens.

 query;  semantic;  web;  automated;  web-based;  

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Abstract: One of the most challenging issues in mining information from the World Wide Web is the design of systems that present the data to the end user by clustering them into meaningful semantic categories. We show that the analysis of the results of a clustering engine can significantly take advantage of enhanced graph drawing and visualization techniques. We propose a graph-based user interface for Web clustering engines that makes it possible for the user to explore and visualize the different semantic categories and their relationships at the desired level of detail

 Visualization;  clustering;  web;  graph;  

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Abstract: Sorry no abstract available for this article

 classification;  facets;  web;  

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Abstract: Ontologies and reasoning are the key terms brought into focus by the semantic web community. Formal representation of ontologies in a common data model on the web can be taken as a foundation for adaptive web technologies as well. This chapter describes how ontologies shared on the semantic web provide conceptualization for the links which are a main vehicle to access information on the web. The subject domain ontologies serve as constraints for generating only those links which are relevant for the domain a user is currently interested in. Furthermore, user model ontologies provide additional means for deciding which links to show, annotate, hide, generate, and reorder. The semantic web technologies provide means to formalize the domain ontologies and metadata created from them. The formalization enables reasoning for personalization decisions. This chapter describes which components are crucial to be formalized by the semantic web ontologies for adaptive web. We use examples from an eLearning domain to illustrate the principles which are broadly applicable to any information domain on the web.

 ontology;  semantic;  web;  semanticweb;  adaptive;  

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Abstract: The large amount of available information on the Web makes it hard for users to locate resources about particular topics of interest. Traditional search tools, e.g., search engines, do not always successfully cope with this problem, that is, helping users to seek the right information. In the personalized search domain, focused crawlers are receiving increasing attention, as a well-founded alternative to search the Web. Unlike a standard crawler, which traverses the Web downloading all the documents it comes across, a focused crawler is developed to retrieve documents related to a given topic of interest, reducing the network and computational resources. This chapter presents an overview of the focused crawling domain and, in particular, of the approaches that include a sort of adaptivity. That feature makes it possible to change the system behavior according to the particular environment and its relationships with the given input parameters during the search.

 search;  web;  adaptive;  focus;  

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Abstract: A very common issue of adaptive Web-Based systems is the modeling of documents. Such documents represent domain-specific information for a number of purposes. Application areas such as Information Search, Focused Crawling and Content Adaptation (among many others) benefit from several techniques and approaches to model documents effectively. For example, a document usually needs preliminary processing in order to obtain the relevant information in an effective and useful format, so as to be automatically processed by the system. The objective of this chapter is to support other chapters, providing a basic overview of the most common and useful techniques and approaches related with document modeling. This chapter describes high-level techniques to model Web documents, such as the Vector Space Model and a number of AI approaches, such as Semantic Networks, Neural Networks and Bayesian Networks. This chapter is not meant to act as a substitute of more comprehensive discussions about the topics presented. Rather, it provides a brief and informal introduction to the main concepts of document modeling, also focusing on the systems that are presented in the rest of the book as concrete examples of the related concepts.

 document;  web;  

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Abstract: There have been many attempts to construct web page recommender systems using collaborative filtering. But the domains these systems can cover are very restricted because it is very difficult to assemble user preference data to web pages, and the number of web pages on the Internet is too large. In this paper, we propose the way to construct a new type of web page recommender system covering all over the Internet, by using Folksonomy and Social Bookmark which are getting very popular in these days.

 query;  tagging;  data-mining;  folksonomy;  recommendations;  web;  

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Abstract: Sorry no abstract available for this article

 document;  web;  similarity;  

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Abstract: This paper presents an automated approach to learning object models by means of useful object data extracted from data-intensive semistructured Web documents such as product descriptions. Modeling intensive data on the Web involves the following three phrases: first, we identify the object region covering the descriptions of object data when irrelevant contents from the Web documents are excluded. Second, we partition the contents of different object data appearing in the object region and construct object data using hierarchical XML outputs. Third, we induce the abstract object model from the analogous object data. This model would match the corresponding object data from a Web site more precisely and comprehensively than the existing handcrafted ontologies. The main contribution of this study is in developing a fully automated approach to extract object data and object model from semistructured Web documents using kernel-based matching and view syntax interpretation. Our system, OnModer, can automatically construct object data and induce object models from complicated Web documents, such as the technical descriptions of personal computers and digital cameras downloaded from manufacturers and vendors sites. A comparison with the available hand-crafted ontologies and tests on an open corpus demonstrate that our framework is effective in extracting meaningful and comprehensive models.

 ontology;  knowledge-discovery;  semantic;  web;  automated;  markup;  

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Abstract: We seek to gain improved insight into how Web search engines shouldcope with the evolving Web, in an attempt to provide users with themost up-to-date results possible. For this purpose we collectedweekly snapshots of some 150 Web sites over the course of one year,and measured the evolution of content and link structure. Our measurements focus on aspects of potential interest to search engine designers: the evolution of link structure over time, the rate ofcreation of new pages and new distinct content on the Web, and the rate of change of the content of existing pages under search-centric measures of degree of change.Our findings indicate a rapid turnover rate of Web pages, i.e.,high rates of birth and death, coupled with an even higher rate ofturnover in the hyperlinks that connect them. For pages that persistover time we found that, perhaps surprisingly, the degree of contentshift as measured using TF.IDF cosine distance does not appear to beconsistently correlated with the frequency of contentupdating. Despite this apparent non-correlation, the rate of content shift of a given page is likely to remain consistent over time. That is, pages that change a great deal in one week will likely change by a similarly large degree in the following week. Conversely, pages that experience little change will continue to experience little change. We conclude the paper with a discussion of the potential implications ofour results for the design of effective Web search engines.

 web;  search engines;  

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Abstract: Due to the recent growth of the World Wide Web, numerous spatio-temporal applications can obtain their required information from web sources. In this demonstration we show The WorldInfo Assistant, an application that extracts and integrates spatial, temporal and other information about different regions of the world from different web sources and databases. This application also provides integration of different vector data with the satellite images of different regions of the world. Finally,...

 spatiotemporal;  Geography;  agents;  knowledge-discovery;  data-mining;  web;  

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Abstract: The evolution of the electronic sources connected through wide area networks like Internet has encouraged the development of new information gathering techniques that go beyond traditional information retrieval and Web search methods. They use advanced techniques, like planning or constraint programming, to integrate and reason about hetereogeneous information sources. In this paper we describe MAPWeb, a multiagent framework that integrates planning agents and Web information retrieval agents....

 agents;  information-retrieval;  web;  webservices;  

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Abstract: This paper discuss topic distillation, an information retrieval problemthat is emerging as a critical task for the www. Algorithms for this problemmust distill a small number of high-quality documents addressing a broadtopic from a large set of candidates.We give a review of the literature, and compare the problem with relatedtasks such as classification, clustering, and indexing. We then describe ageneral approach to topic distillation with applications to searching andpartitioning, based on the algebraic properties of matrices derived fromparticular documents within the corpus. Our method – which we call special filtering – combines the use of terms, hyperlinks and anchor-textto improve retrieval performance. We give results for broad-topic querieson the www, and also give some anecdotal results applying the sametechniques to US Supreme Court law cases, US patents, and a set of WallStreet Journal newspaper articles.

 document;  knowledge-discovery;  data-mining;  web;  library;  

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Abstract: This paper discusses several data mining algorithms and techniques thatwe have developed at the University of Arizona Artificial Intelligence Lab.We have implemented these algorithms and techniques into severalprototypes, one of which focuses on medical information developed incooperation with the National Cancer Institute (NCI) and the University ofIllinois at Urbana-Champaign. We propose an architecture for medicalknowledge information systems that will permit data mining across severalmedical information sources and discuss a suite of data mining tools that weare developing to assist NCI in improving public access to and use of theirexisting vast cancer information collections.

 cancer;  health;  SOM;  data-mining;  web;  

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Abstract: Sorry no abstract available for this article

 classification;  agents;  document;  query;  information-retrieval;  web;  

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Abstract: Sorry no abstract available for this article

 classification;  agents;  exploration;  document;  knowledge-discovery;  web;  

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Abstract: This paper details efforts to development a set of prototype, web-based geovisualisation tools. The focus is on design and implementation of lightweight tools that can run in standard web browsers and access data, stored in a remote database. The web geo-visualisation tools incorporate several standard exploratory spatial data analysis methods, including linked brushing and interactive animation. These tools are constructed using Macromedia Flash, a commercial software application that produces ...

 Geovisualization;  web;  exploratory;  

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