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Panyr, J.: Automatische Klassifikation und Information Retrieval : Anwendung und Entwicklung komplexer Verfahren in Information-Retrieval-Systemen und ihre Evaluierung (1986) 0.02

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Panyr, J.: ¬Die Theorie der Fuzzy-Mengen und Information-Retrieval-Systeme (1986) 0.02

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Panyr, J.: Information Retrieval Systeme : state of the art (1987) 0.02

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Panyr, J.: Vektorraum-Modell und Clusteranalyse in Information-Retrieval-Systemen (1987) 0.02
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Abstract

Ausgehend von theoretischen Indexierungsansätzen wird das klassische Vektorraum-Modell für automatische Indexierung (mit dem Trennschärfen-Modell) erläutert. Das Clustering in Information-Retrieval-Systemem wird als eine natürliche logische Folge aus diesem Modell aufgefaßt und in allen seinen Ausprägungen (d.h. als Dokumenten-, Term- oder Dokumenten- und Termklassifikation) behandelt. Anschließend werden die Suchstrategien in vorklassifizierten Dokumentenbeständen (Clustersuche) detailliert beschrieben. Zum Schluß wird noch die sinnvolle Anwendung der Clusteranalyse in Information-Retrieval-Systemen kurz diskutiert

Panyr, J.: Information-Retrieval-Methoden in regelbasierten Expertensystemen (1990) 0.02

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Panyr, J.: Objektzentrierte Wissensrepräsentation und Information-Retrieval-Methoden (1992) 0.02

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Panyr, J.: Relevanzproblematik in Information-Retrieval-Systemen (1986) 0.01
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Abstract

Die Relevanzproblematik gehört zu den Schlüsselthemen der Theorie und Praxis der Information-Retrieval-Systeme. Ausgehend vom probabilistischen Relevanzbegriff wird versucht, die verschiedenen Relevanzauffassungen (d.h. Relevanzgrad, Relevanzwahrscheinlichkeit bzw. Pertinenzbewertung) in ein gemeinsames Schema einzuordnen. Dabei wird auf die verschiedenen Arten der Relevanzbeurteilungen, die die Basis für die unterschiedlichen Relevanzauffassungen bilden, sowie auf die Bedeutung des Relevanzbegriffs in sog. wissensbasierten Systemen kurz eingegangen. Als die geeignete Vorgehensweise, die die verschiedenen Relevanzauffassungen zu vereinigen ermöglicht, wird eine interaktive Relevanzfeedback-Strategie betrachtet

Panyr, J.: Vom Wissen zur Information : Notwendigkeit der Kooperation der Fachleute aus dem Bereich der Informations-Retrieval-Systeme und der Systeme mit formaler Intelligenz (1988) 0.01

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Panyr, J.: Information retrieval techniques in rule-based expert systems (1991) 0.01
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Abstract

In rule-based expert systems knowledge is represented in an IF-THEN form: IF <set of conditions> THEN <decision>. A limited subset of natural language - supplemented by specified relations and operators - is used to formulate the rules. Rule syntax is simple. This makes it easy to acquire knowledge through an expert and permits plausibility checks on the knowledge base without the expert having knowledge of the implementation language or details of the system. A number of steps are used to to select suitable rules during the rule-matching process. It is noteworthy that rules are well structured documents for an information retrieval system, particularly since the number of rules in a rule-based system remains manageable. In this paper it will be shown that this permits automatic processing of the rule set by methods of information retrieval (i.e. automatic indexing and automatic classification of rules, automatic thesaurus construction to the knowledge base). A knowledge base which is processed and structured in this fashion allows use of a complex application-specific search strategy and hence an efficient and effective realization of reasoning mechanisms

Panyr, J.: Probabilistische Modelle in Information-Retrieval-Systemen (1986) 0.01

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Panyr, J.: Automatische thematische Textklassifikation und ihre Interpretation in der Dokumentengrobrecherche (1980) 0.01
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Abstract

Für die automatische Erschließung natürlich-sprachlicher Dokumente in einem Informationssystem wurde ein Verfahren zur automatischen thematischen hierarchischen Klassifikation der Texte entwickelt. Die dabei gewonnene Ordnungsstruktur (Begriffsnetz) wird beim Retrieval als Recherchehilfe engeboten. Die Klassifikation erfolgt in vier Stufen: Textindexierung, Prioritätsklassenbildung, Verknüpfung der begriffe und Vernetzung der Prioritätsklassen miteinander. Die so entstandenen Wichtigkeitsstufen sind die Hierarchieebenen der Klassifikation. Die während des Clusteringverfahrens erzeugten Begriffs- und Dokumenten-Gruppierungen bilden die Knoten des Klassifikationsnetzes. Die Verknüpfung zwischen den Knoten benachbarter Prioritätsklassen repräsentieren die Netzwege in diesem Netz. Die Abbildung der Suchfrage auf dieses Begriffsnetz wird zur Relevanzbeurteilung der wiedergewonnenen Texte benutzt

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