Nutzungspotentiale interner Weblogs bei RobinBook.ch

Die interne Kommunikation ist ein zentrales Element erfolgreicher Unternehmensführung. Sie generiert Wissen, welches für die Innovations- und Produktivitätskraft eines Unternehmens entscheidend ist. Je grösser und internationaler dieses jedoch ist, desto schwieriger wird die Vernetzung der Mitarbeiter und der Austausch von Wissen. Heutzutage bietet das Web 2.0 durch interaktive und kollaborative Elemente Wege für einen offenen und transparenten Informationsfluss. Weblogs, Soziale Netzwerke oder Wikis sind beliebte Werkzeuge der Verbreitung von Informationen und Förderung eines kommunikativen Austauschs, da sie durch einfache Bedienung nicht nur IT- Spezialisten vorbehalten sind. In diesem Beitrag wird anhand eines Fallbeispiels gezeigt, wie durch einen intern genutzten Weblog (kurz Blog) eine Alternative zum herkömmlichen Intranet geboten werden kann, um Unternehmen zu vernetzen und dadurch einen Wissensaustausch zu ermöglichen.

Wie Social Media unser Gehirn verändert

Sind Sie es gewohnt, Ihre News in 140 Zeichen zu erhalten? Zeigen Sie all Ihren Freunden (mehr oder weniger) öffentlich, was Sie gerne haben? ... oder schauen Sie regelmäßig Videos unter 10 Minuten Länge an? Falls Sie eine (oder gleich mehrere) dieser Fragen mit Ja beantwortet haben, könnte es gut sein, dass sich die Funktionsweise Ihres Gehirns in den letzten Jahren bereits verändert hat.

Customized mashups for improved reputation visualization

This document describes a possible use for the YouReputation API. A mashup combining the YouReputation and the Flickr APIs attempts to improve the visualization of reputation. First, this paper gives an introduction to Web services and APIs and further explains the developed prototype. This paper introduces an API that can be easily combined with other APIs to improve the representation of reputation terms and therefore enhance usability and design.

A distributed, semiotic-inductive and human-Oriented approach to web-scale knowledge retrieval

Web-scale knowledge retrieval can be enabled by distributed information retrieval, clustering Web clients to a large-scale computing infrastructure for knowledge discovery from Web documents. Based on this infrastructure, we propose to apply semiotic (i.e., sub-syntactical) and inductive (i.e., probabilistic) methods for inferring concept associations in human knowledge. These associations can be combined to form a fuzzy (i.e.,gradual) semantic net representing a map of the knowledge in the Web. Thus, we propose to provide interactive visualizations of these cognitive concept maps to end users, who can browse and search the Web in a human-oriented, visual, and associative interface.

The FORA Framework - A Fuzzy Grassroots Ontology for Online Reputation Management

Online reputation management deals with monitoring and influencing the online record of a person, an organization or a product. The Social Web offers increasingly simple ways to publish and disseminate personal or opinionated information, which can rapidly have a disastrous influence on the online reputation of some of the entities. This dissertation can be split into three parts: In the first part, possible fuzzy clustering applications for the Social Semantic Web are investigated. The second part explores promising Social Semantic Web elements for organizational applications,while in the third part the former two parts are brought together and a fuzzy online reputation analysis framework is introduced and evaluated. Theentire PhD thesis is based on literature reviews as well as on argumentative-deductive analyses.The possible applications of Social Semantic Web elements within organizations have been researched using a scenario and an additional case study together with two ancillary case studies—based on qualitative interviews. For the conception and implementation of the online reputation analysis application, a conceptual framework was developed. Employing test installations and prototyping, the essential parts of the framework have been implemented.By following a design sciences research approach, this PhD has created two artifacts: a frameworkand a prototype as proof of concept. Bothartifactshinge on twocoreelements: a (cluster analysis-based) translation of tags used in the Social Web to a computer-understandable fuzzy grassroots ontology for the Semantic Web, and a (Topic Maps-based) knowledge representation system, which facilitates a natural interaction with the fuzzy grassroots ontology. This is beneficial to the identification of unknown but essential Web data that could not be realized through conventional online reputation analysis. Theinherent structure of natural language supports humans not only in communication but also in the perception of the world. Fuzziness is a promising tool for transforming those human perceptions intocomputer artifacts. Through fuzzy grassroots ontologies, the Social Semantic Web becomes more naturally and thus can streamline online reputation management.

Fuzzy Online Reputation Analysis Framework

The fuzzy online reputation analysis framework, or “foRa” (plural of forum, the Latin word for marketplace) framework, is a method for searching the Social Web to find meaningful information about reputation. Based on an automatic, fuzzy-built ontology, this framework queries the social marketplaces of the Web for reputation, combines the retrieved results, and generates navigable Topic Maps. Using these interactive maps, communications operatives can zero in on precisely what they are looking for and discover unforeseen relationships between topics and tags. Thus, using this framework, it is possible to scan the Social Web for a name, product, brand, or combination thereof and determine query-related topic classes with related terms and thus identify hidden sources. This chapter also briefly describes the youReputation prototype (www.youreputation.org), a free web-based application for reputation analysis. In the course of this, a small example will explain the benefits of the prototype.

Towards an Emergent Semantic Web

In his in uential article about the evolution of the Web, Berners-Lee [1] envisions a Semantic Web in which humans and computers alike are capable of understanding and processing information. This vision is yet to materialize. The main obstacle for the Semantic Web vision is that in today's Web meaning is rooted most often not in formal semantics, but in natural language and, in the sense of semiology, emerges not before interpretation and processing. Yet, an automated form of interpretation and processing can be tackled by precisiating raw natural language. To do that, Web agents extract fuzzy grassroots ontologies through induction from existing Web content. Inductive fuzzy grassroots ontologies thus constitute organically evolved knowledge bases that resemble automated gradual thesauri, which allow precisiating natural language [2]. The Web agents' underlying dynamic, self-organizing, and best-effort induction, enable a sub-syntactical bottom up learning of semiotic associations. Thus, knowledge is induced from the users' natural use of language in mutual Web interactions, and stored in a gradual, thesauri-like lexical-world knowledge database as a top-level ontology, eventually allowing a form of computing with words [3]. Since when computing with words the objects of computation are words, phrases and propositions drawn from natural languages, it proves to be a practical notion to yield emergent semantics for the Semantic Web. In the end, an improved understanding by computers on the one hand should upgrade human- computer interaction on the Web, and, on the other hand allow an initial version of human- intelligence amplification through the Web.

Führungsinformationssysteme unter Nutzung der unscharfen Logik – Fallbeispiel coop@home

Entscheidungsfragen lassen sich bei anspruchsvollen Managementaufgaben nicht immer scharf mit ja oder nein beantworten. Vielmehr geht es um ein Abwägen unterschiedlicher Einflussfaktoren und die Antwort für eine Problemlösung lautet oft ‚ja unter Vorbehalt' oder ‚sowohl als auch´. Die Antwort ist unscharf und kann Werte zwischen 0 und 1 annehmen. Die unscharfe Logik entspricht der menschlichen Wahrnehmung. Sie vermag neben quantitativen Grössen qualitative Einschätzungen mit einzubeziehen. Um Entscheidungsfindung bei vagem Sachverhalt in Informationssystemen zu ermöglichen, müssen Managementmethoden mit unscharfen Konzepten erweitert werden. Der Beitrag führt in die unscharfe Logik ein und zeigt deren Potenzial anhand der unscharfen Scoringmethode fRFM (fuzzy Recency-, Frequency- und Monetary-Werte) auf, die beim schweizerischen Detailhändler coop@home testweise angewendet wurde.

Blogosphäre - Soziale Netzwerke als Trendsetter

Seit kurzem erweitert sich das Web zu einem neuen Lebensraum, in welchem sich Nutzer präsentieren, mit anderen treffen, Informationen und Know-how austauschen, gemeinsame Projekte verfolgen und kulturelle Barrieren überwinden können. Unser Beitrag gibt einen kurzen Überblick über soziale Netzwerke, wobei das Augenmerk vor allem auf Weblogs und Onlinegemeinschaften der Blogosphäre gelegt wird. Durch die in Weblogs gängige Funktion Kommentare mit Links zu eigenen Blogs zu hinterlassen, wird eine Gemeinschaftsbildung gefördert, wobei Onlinegemeinschaften, deren Themen sich beispielsweise um Gadgets, Digitalfotografie, Fashion, Gastronomie, Sport, Musik, usw. drehen, entstehen können. Anhand verschiedener Praxisbeispiele wird aufgezeigt wie in Bloggemeinschaften Trends gesetzt werden, welche später wiederum von Suchmaschinen an die breite Öffentlichkeit getragen werden. Abrundend präsentieren wir Handlungsempfehlungen für den Umgang mit sozialen Netzwerken der Blogosphäre.

A fuzzy grassroots ontology for improving social semantic web search

The web is continuously evolving into a collection of many data, which results in the interest to collect and merge these data in a meaningful way. Based on that web data, this paper describes the building of an ontology resting on fuzzy clustering techniques. Through continual harvesting folksonomies by web agents, an entire automatic fuzzy grassroots ontology is built. This self-updating ontology can then be used for several practical applications in fields such as web structuring, web searching and web knowledge visualization.A potential application for online reputation analysis, added value and possible future studies are discussed in the conclusion.

Prometheus Framework for Fuzzy Information Retrieval in Semantic Spaces

This paper introduces a novel vision for further enhanced Internet of Things services. Based on a variety of data (such as location data, ontology-backed search queries, in- and outdoor conditions) the Prometheus framework is intended to support users with helpful recommendations and information preceding a search for context-aware data. Adapted from artificial intelligence concepts, Prometheus proposes user-readjusted answers on umpteen conditions. A number of potential Prometheus framework applications are illustrated. Added value and possible future studies are discussed in the conclusion.

A Fuzzy Grassroots Ontology for improving Weblog Extraction

This paper presents fuzzy clustering algorithms to establish a grassroots ontology – a machine-generated weak ontology – based on folksonomies. Furthermore, it describes a search engine for vaguely associated terms and aggregates them into several meaningful cluster categories, based on the introduced weak grassroots ontology. A potential application of this ontology, weblog extraction, is illustrated using a simple example. Added value and possible future studies are discussed in the conclusion.

Extraktion und kartographische Visualisierung von Informationen aus Weblogs

Beim Information Retrieval ist in Anbetracht der Informationsflut entscheidend, relevante Informationen zu finden. Ein vielversprechender Ansatz liegt im Semantischen Web, wobei dem System die Bedeutung von Informationen ontologiebasiert beigebracht wird. Sucht der Benutzer nach Stichworten, werden ihm anhand der Ontologie verwandte Begriffe angezeigt und er kann mittels Mensch-Maschine-Interaktion seine relevanten Informationen extrahieren. Um eine solche Interaktion zu fördern, werden die Ergebnisse visuell aufgearbeitet. Dabei liegt der Mehrwert darin, dass der Benutzer anstelle von Tausenden von Suchresultaten in einer fast endlosen Liste, ein kartographisch visualisiertes Suchresultat geliefert bekommt. Dabei hilft die Visualisierung, unvorhergesehene Beziehungen zu entdecken und zu erforschen.

Prometheus – Fuzzy Information Retrieval for Semantic Homes and Environments

This paper introduces a novel vision for further enhanced Internet of Things services. Based on a variety of data – such as location data, ontology-backed search queries, in- and outdoor conditions – the Prometheus framework is intended to support users with helpful recommendations and information preceding a search for context-aware data. Adapted from artificial intelligence concepts, Prometheus proposes user-readjusted answers on umpteen conditions. A number of potential Prometheus framework applications are illustrated. Added value and possible future studies are discussed in the conclusion.

Weblog extraction with fuzzy classification methods

This paper uses folksonomies and fuzzy clustering algorithms to establish term-relevant related results. This paper will propose a Meta search engine with the ability to search for vaguely associated terms and aggregate them into several meaningful cluster categories. The potential of the fuzzy weblog extraction is illustrated using a simple example and added value and possible future studies are discussed in the conclusion.