BibSonomy publications for /tag/studienarbeitFri Dec 02 10:44:22 CET 2011Technische Universität IlmenauVersuchsaufbau einer haptischen Informationsschnittstelle zur Durchführung von NutzertestsStudienarbeit2007Assistenzsystem Audacity Bauelemente Behinderte Biomechatronik Cadsoft EAGLE HMI Hardware Ilmenau Informationsschnittstelle InnoRegio Instruments LabView Layout Leiterplatte Maschinenbau Mechatronik Mensch-Maschine-Schnittstelle Menschen Modellregion National Nutzertests Schaltung Sehstörungen Software Studienarbeit TAS TU Thüringer Touristisches Versuchsaufbau VisualGPS Wald barrierefrei blind haptisch human-machine_interface own schwerhörig Thu Feb 17 17:42:31 CET 2011International Conference on Computational Sciencebibsource: DBLP, http://dblp.uni-trier.de513-520Collaborative Web Browsing Based on Ontology Learning from Bookmarks.2004closely_related studienarbeit ol_web2.0 widely_related This paper proposes the collaborative web browsing system sharing knowledge with other users. We have specifically focused on user interests extracted from bookmarks. A simple URL based-bookmark is provided with structural information by the conceptualization of the ontology. Furthermore, ontology learning based on a hierarchical clustering method can be applied to handle dynamic changes in bookmarks. As a result of our experiments, with respect to recall, about 53.1% of the total time was saved during collaborative browsing for seeking the equivalent set of information, as compared with single web browsing.Thu Feb 17 17:42:19 CET 2011Las Vegas, Nevada USAProceedings of the 3rd International Conference on Universal A ccess in Human-Computer Interaction (UAHCI)22-27 JulyUsage-driven Evolution of Personal Ontologies2005studienarbeit ol_web2.0 widely_related Large information repositories as digital libraries, online shops, etc. rely on a taxonomy of the objects under consideration to structure the vast contents and facilitate browsing and searching (e.g., ACM topic classification for computer science literature, Amazon product taxonomy, etc.). As in heterogeneous communities users typically will use different parts of such an ontology with varying intensity, customization and personalization of the ontologies is desirable. In this paper we adapt a collaborative filtering recommender system to assist users in the management and evolution of their personal ontology by providing detailed suggestions of ontology changes. Such a system has been implemented in the context of Bibster, a peer-to-peer based personal bibliography management tool. Finally, we report on an in-situ experiment with the Bibster community that shows the performance improvements over non-personalized recommendations.Wed Feb 09 14:55:06 CET 2011New York, NY, USAAAMAS '02: Proceedings of the first international joint conference on Autonomous agents and multiagent systems1137--1138A multi-agent system for collaborative bookmarking2002bookmarks cbr classifier closely_related collaborative_interface_agents hybrid_neural-CBR_classification studienarbeit In this paper we describe a new distributed collaborative bookmark system, called COWING (for COllaborative Web IndexING system). The COWING system is composed of a set of assistant agents, called WINGS, and a central agent that manages the user's organization. Each user is assisted by a Wing agent that performs two tasks: learning the user's strategy in classifying her/his own bookmarks and interacting with other WING agents in order to fetch new bookmarks that match the local user information need.Wed Feb 09 14:55:03 CET 2011Paris, FranceProceedings of the International Conference on Computer Assisted Information Retrieval (RIAO)Informing the design of shared bookmark systems2000closely_related studienarbeit Bookmark systems are now recognised as a practical mean that allow users to land mark interesting sites in the huge information space that constitute the World Wide Web. In this paper we argue that, by building collaborative bookmark management tools where a group of people can share their experiences and their results in feeding and organising personal bookmark sets, bookmarks can be transformed into effective customized web spaces. In this paper we first present a study of main requirements that a shared bookmark system should meet. Then the design space of such applications is analysed. The set of identified requirements is used to compare and criticise main collaborative shared bookmark systems that are proposed in the literature. Main drawbacks of existing systems are a) the weak customisation of shared spaces, b) the lack of efficient and easy to use privacy protection policies, and c) the adoption of centralised architectures that affects badly responsiveness, availability and d...Wed Feb 09 14:54:52 CET 2011Metainformaticsbibsource: DBLP, http://dblp.uni-trier.de42-48Babylon Bookmarks: A Taxonomic Approach to the Management of WWW Bookmarks.2002closely_related studienarbeit Taxonomic reasoning can be a useful organization paradigm to address issues dealing with the management of WWW bookmarks. Management of WWW bookmarks comprise one of the most frequent activities of WWW users. In this paper, "Babylon Bookmarks" are presented allowing users to apply taxonomic reasoning on WWW bookmarks. "Babylon Bookmarks" is based on the "Babylon System," an infrastructure to support general taxonomic reasoning tasks. The "Babylon System" allows the development of arbitrary taxonomic services based on Open Hypermedia Specifications.Wed Feb 09 14:54:43 CET 2011Computer Networksbibsource: DBLP, http://dblp.uni-trier.de8-131103-1114A Bookmarking Service for Organizing and Sharing URLs.291997closely_related studienarbeit Web browser bookmarking facilities predominate as the method of choice for managing URLs. In this paper, we describe some deficiencies of current bookmarking schemes, and examine an alternative to current approaches. We present WebTaggerTM, an implemented prototype of a personal bookmarking service that provides both individuals and groups with a customizable means of organizing and accessing Web-based information resources. In addition, the service enables users to supply feedback on the utility of these resources relative to their information needs, and provides dynamically-updated ranking of resources based on incremental user feedback. Individuals may access the service from anywhere on the Internet, and require no special software. This service greatly simplifies the process of sharing URLs within groups, in comparison with manual methods involving email. The underlying bookmark organization scheme is more natural and flexible than current hierarchical schemes supported by the major Web browsers, and enables rapid access to stored bookmarks.Tue Feb 08 15:56:03 CET 2011New York, NY, USAProceedings of the SIGCHI conference on Human factors in computing systems41-48Information Archiving with Bookmarks: Personal Web Space Construction and Organization1998studienarbeit information_space bookmark background www Bookmarks are used as "personal Web information spaces" to help people remember and retrieve interesting Web pages. A study of personal Web information spaces surveyed 322 Web users and analyzed the bookmark archives of 50 Web users. The results of this study are used to address why people make bookmarks, and how they create, use, and organize them. Recommendations for improving the organization, visualization, representation, and integration of bookmarks are provided. The recommendations include simple mechanisms for filing bookmarks at creation time, the use of time-based visualizations with automated filters, the use of contextual information in representing bookmarks, and the combination of hierarchy formation and Web page authoring to aid in organizing and viewing bookmarks.Tue Feb 08 15:55:59 CET 2011Atlanta, GA, USAProceedings of the CHI97: Conference on Human Factors in Computing SystemsMarch 22-27How People Use WWW bookmarks1997user_study studienarbeit bookmark informatin_space background www In this detailed empirical study of WWW browsing and bookmarks we define a personal information space as having five basic properties paralleling those of a larger complex information space. We describe user behavior on the Web and show how a user's bookmark archive is a personal Web information space.Fri Jan 28 16:26:42 CET 2011Special Issue of the Computer Networks journal on Innovations in Web Communications Infrastructure164574--4585Supporting Collaborative Hierarchical Classification: Bookmarks as an Example512007studienarbeit 2007 myown itegpub Bookmarks (or favorites, hotlists) are popular strategies to relocate interesting websites on the WWW by creating a personalized URL repository. Most current browsers offer a facility to locally store and manage bookmarks in a hierarchy of folders; though, with growing size, users reportedly have trouble to create and maintain a stable organization structure. This paper presents a novel collaborative approach to ease bookmark management, especially the “classification�? of new bookmarks into a folder. We propose a methodology to realize the collaborative classification idea of considering how similar users have classified a bookmark. A combination of nearest-neighbor-classifiers is used to derive a recommendation from similar users on where to store a new bookmark. A prototype system called CariBo has been implemented as a plugin for the central bookmark server software SiteBar. All findings have been evaluated on a reasonably large scale, real user dataset with promising results, and possible implications for shared and social bookmarking systems are discussed.Fri Jan 28 16:26:42 CET 2011Edinburgh, ScotlandProceedings of the 2nd Workshop in Innovations in Web Infrastructure (IWI2) at WWW2006Mayisbn = {085432853X}Automatic Bookmark Classification - A Collaborative Approach2006studienarbeit www2006 2006 myown iwi itegpub Bookmarks (or Favorites, Hotlists) are a popular strategy to relocate interesting websites on the WWW by creating a personalized local URL repository. Most current browsers offer a facility to store and manage bookmarks in a hierarchy of folders; though, with growing size, users reportedly have trouble to create and maintain a stable taxonomy. This paper presents a novel collaborative approach to ease bookmark management, especially the “classification�? of new bookmarks into a folder. We propose a methodology to realize the collaborative classification idea of considering how similar users have classified a bookmark. A combination of nearest-neighbour-classifiers is used to derive a recommendation from similar users on where to store a new bookmark. Additionally, a procedure to generate keyword recommendations is proposed to ease the annotation of new bookmarks. A prototype system called CariBo has been implemented as a plugin of the central bookmark server software SiteBar. A case study conducted with real user data supports the validity of the approach.Fri Jan 28 11:35:31 CET 2011Proceedings of the 14$^{th}$ Conference on Uncertainty in Artificial Intelligence43-52Empirical Analysis of Predictive Algorithms for Collaborative Filtering.1998studienarbeit Fri Jan 28 11:35:22 CET 2011Como, ItalyProc. of WSDAAL (Workshop su Sistemi distribuiti, algoritmi, architetture e linguaggi)An Architecture for Advanced Bookmark Management2001studienarbeit closely_related Fri Jan 28 11:35:21 CET 2011Los Alamitos, CA, USAProceedings of the 3rd Int'l. Conf. on Advanced Learning Technologies91--95InLinx for document classification, sharing and recommendation2003studienarbeit closely_related This paper proposes an hybrid recommender system, InLinx, that combine content analysis and the development of virtual clusters of students and of didactical sources providing facilities to use the huge amount of digital information according to the student’s personal requirements and interests. The paper proposes novel methods for information management, with special focus on the development of new algorithms and intelligent applications for personalized information sharing, filtering and retrieval. InLinx helps the student to classify domain specific information found in the Web and saved as bookmarks, to recommend these documents to other students with similar interests and to periodically notify new potential interesting documents.Fri Jan 28 11:35:21 CET 2011Mining themes from bookmarks2000studienarbeit closely_related Many Web surfers maintain bookmark files containing URLs organized into folders which represent topics by function or content. We propose a new framework for discovering themes among such folders created by a community of surfers with overlapping interests. In principle, surfers need not create personal folders; they can just use a 'standard' tax- onomy such as Yahoo. In practice, a standard taxonomy is neither necessary nor sufficient; it is too detailed in most part, but likely to be inadequate in the community's areas of deep interest. Our framework, based on the minimum de- scription length principle, exploits two semantically different relations: "term occurs in document" and "document occurs in folder", and combines them without the need for heuris- tic weighting of attributes. Themes, in effect, finds common factors in people's interests when it can, while maintaining their individuality when it must. We present experimen- tal results to illustrate our framework and show how it is different from content-based clustering. We also propose a number of applications to finding themes, including collab- orative recommendation and resource discovery.Fri Jan 28 11:35:20 CET 2011International Journal of Human-Computer Studies903--922What do Web users do? An empirical analysis of Web use542002studienarbeit navigation revisitation background www This paper provides an empirical characterization of user actions at the web browser. The study is based on an analysis of 4 months of logged client-side data that describes user actions with recent versions of Netscape Navigator. In particular, the logged data allow us to determine the title, URL and time of each page visit, how often they visited each page, how long they spent at each page, the growth and content of bookmark collections, as well as a variety of other aspects of user interaction with the web. The results update and extend prior empirical characterizations of web use. Among the results we show that web page revisitation is a much more prevalent activity than previously reported (approximately 81% of pages have been previously visited by the user), that most pages are visited for a surprisingly short period of time, that users maintain large (and possibly overwhelming) bookmark collections, and that there is a marked lack of commonality in the pages visited by different users. These results have implications for a wide range of web-based tools including the interface features provided by web browsers, the design of caching proxy servers, and the design of efficient web sites.Fri Jan 28 11:35:20 CET 2011Proceedings of RIAO2000AprilAn annotation tool for Web browsers and its applications to information retrieval2000studienarbeit widely_related With bookmark programs, current Web browsers provide a limited support to personalize the Web. We present a new Web annotation tool which uses the Document Object Model Level 2 and Dynamic HTML to deliver a system where speed and privacy are important issues. We report on several experiments showing how annotations improve document access and retrieval by providing user-directed document summaries. Preliminary results also show that annotations can be used to produce user-directed document clustering and classification.Fri Jan 28 11:35:18 CET 2011Using semantic treemaps to categorize and visualize bookmark files2002studienarbeit closely_related As more and more information is available on the Internet, search engines and bookmark tools become very popular. However, most search tools are based on character-level matching without any semantic analysis, and users have to manually organize their bookmarks or favorite collections without any convenient tool to help them identify the subjects of the Web pages. In this paper, we introduce an interactive tool that automatically analyzes, categorizes, and visualizes the semantic relationships of web pages in personal bookmark or favorites collections based on their semantic similarity. Sophisticated data analysis methods are applied to retrieve and analyze the full text of the Web pages. The Web pages are clustered hierarchically based on their semantic similarities . A utility measure is recursively applied to determine the best partitions that are visualized by what we call the Semantic Treemap. Various interaction methods such as scrolling, zooming, expanding, selecting, searching, filtering etc. are provided to facilitate viewing and querying for information. Furthermore, the hierarchical organization as well as the semantic similarities among Web pages can be exported and visualized in a collaborative 3D environment, allowing a group of people to compare and share each other's bookmarks.Fri Jan 28 11:35:00 CET 2011London, UKWI '01: Proceedings of the First Asia-Pacific Conference on Web Intelligence: Research and Development95--105A Rough Set-Aided System for Sorting WWW Bookmarks2001studienarbeit closely_related Most people store 'bookmarks' to web pages. These allow the user to return to a web page later on, without having to remem- ber the exact URL address. People attempt to organise their bookmark databases by filing bookmarks under categories, themselves arranged in a hierarchical fashion. As the maintenance of such large repositories is diffcult and time-consuming, a tool that automatically categorises book- marks is required. This paper investigates how rough set theory can help extract information out of this domain, for use in an experimental auto- matic bookmark classification system. In particular, work on rough set dependency degrees is applied to reduce the otherwise high dimensional- ity of the feature patterns used to characterize bookmarks. A compari- son is made between this approach to data reduction and a conventional entropy-based approach.Fri Jan 28 11:35:00 CET 2011Chemnitz, DEProceedings of {ECML}-98, 10th European Conference on Machine Learning1398137--142Text categorization with support vector machines: learning with many relevant features1998studienarbeit eventually_useful This paper explores the user of Support Vector machines (SVMs) for learning text classifiers from examples. It analyzes the particular properties of learning with text data and identifies, why SVMs are appropriate for this task. Empirical results support the theoretical findings. SVMs achieve substantial improvements over the currently best performing methods and they behave robustly over a variety of different learning tasks. Furthermore, they are fully automatic, eliminating the need for manuar parameter tuning.studienarbeitCommunity for tag(s) studienarbeit