Search (52 results, page 1 of 3)

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Abstract

Durch die zunehmende Mediatisierung und Digitalisierung wird die moderne Gesellschaft immer mehr mit dem Thema der Informationsüberflutung konfrontiert. Erstaunlicherweise führt der Zuwachs an Informationen gleichzeitig zu einem Mangel an Wissen. Die Erklärung kann darin gefunden werden, dass ein großer Teil der existierenden Informationen nicht aufgefunden werden kann. Es handelt sich meistens um Informationen die auf semi- und nichtstrukturierte Daten beruhen. Schätzungen zufolge sind heute rund 80% der entscheidungsrelevanten Informationen in Unternehmen in unstrukturierter, d. h. meist textueller Form vorhanden. Die Unfähigkeit der Maschinen den Inhalt unstrukturierter Texte zu verstehen führt dazu, dass dokumentiertes Wissen schwer auffindbar ist und oft unentdeckt bleibt. Wegen des Informationsvolumens, das meistens zu groß ist, um gelesen, verstanden oder sogar benutzt zu werden, ergibt sich folgendes Problem, mit dem man konfrontiert wird: Informationen die nicht in Wissen umgewandelt werden können, bleiben als papiergebundene oder digitale Dokumente in Data-Repositories verschlossen. Angesichts der heute anfallenden Menge an Dokumenten erscheint eine manuelle Vergabe von Schlagworten nicht mehr realistisch. Deshalb entwickelt Wissensmanagement unterstützende Verfahren, die Informationen rechtzeitig, in der richtigen Qualität und den richtigen Personen verfügbar machen. Einige Schwerpunkte an denen zur Zeit geforscht wird, sind Modelle zur Repräsentation von Dokumenten, Methoden zur Ähnlichkeitsbestimmung von Anfragen zu Dokumenten und zur Indexierung von Dokumentenmengen, sowie die automatische Klassifikation. Vor diesem Hintergrund konzentriert sich diese Arbeit auf die unterschiedlichen Verfahren der automatischen Indexierung, hebt die algorithmischen Vor- und Nachteile hervor, mit dem Ziel die Funktionsweise im Bereich der unstrukturierten Texte zu analysieren. Hierfür erfolgt im 3. Kapitel eine genauere Untersuchung und Darstellung automatischer Indexierungsverfahren. Zuvor werden in Kapitel 2 grundlegende Begrifflichkeiten erklärt, eingeordnet und abgegrenzt. Abschließend werden anhand der theoretischen Darlegung Implementierungen der vorgestellten Verfahren kurz beschrieben. Die Ausarbeitung endet mit der Schlussfolgerung und dem Ausblick.

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Source

Information retrieval. 2(2000), S.165-176

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Source

Auf dem Weg zur Informationskultur: Wa(h)re Information? Festschrift für Norbert Henrichs zum 65. Geburtstag, Hrsg.: T.A. Schröder

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Source

Bulletin of the American Society for Information Science. 28(2002) no.1, S.12-15

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Source

Information outlook. 9(2005) no.8, S.22-23

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Abstract

The introduction and growth of the World Wide Web (WWW, or Web) have resulted in a profound change in the way individuals and organizations access information. In terms of volume, nature, and accessibility, the characteristics of electronic information are significantly different from those of even five or six years ago. Control of, and access to, this flood of information rely heavily an automated techniques for indexing and retrieval. According to Gudivada, Raghavan, Grosky, and Kasanagottu (1997, p. 58), "The ability to search and retrieve information from the Web efficiently and effectively is an enabling technology for realizing its full potential." Almost 93 percent of those surveyed consider the Web an "indispensable" Internet technology, second only to e-mail (Graphie, Visualization & Usability Center, 1998). Although there are other ways of locating information an the Web (browsing or following directory structures), 85 percent of users identify Web pages by means of a search engine (Graphie, Visualization & Usability Center, 1998). A more recent study conducted by the Stanford Institute for the Quantitative Study of Society confirms the finding that searching for information is second only to e-mail as an Internet activity (Nie & Ebring, 2000, online). In fact, Nie and Ebring conclude, "... the Internet today is a giant public library with a decidedly commercial tilt. The most widespread use of the Internet today is as an information search utility for products, travel, hobbies, and general information. Virtually all users interviewed responded that they engaged in one or more of these information gathering activities."
Techniques for automated indexing and information retrieval (IR) have been developed, tested, and refined over the past 40 years, and are well documented (see, for example, Agosti & Smeaton, 1996; BaezaYates & Ribeiro-Neto, 1999a; Frakes & Baeza-Yates, 1992; Korfhage, 1997; Salton, 1989; Witten, Moffat, & Bell, 1999). With the introduction of the Web, and the capability to index and retrieve via search engines, these techniques have been extended to a new environment. They have been adopted, altered, and in some Gases extended to include new methods. "In short, search engines are indispensable for searching the Web, they employ a variety of relatively advanced IR techniques, and there are some peculiar aspects of search engines that make searching the Web different than more conventional information retrieval" (Gordon & Pathak, 1999, p. 145). The environment for information retrieval an the World Wide Web differs from that of "conventional" information retrieval in a number of fundamental ways. The collection is very large and changes continuously, with pages being added, deleted, and altered. Wide variability between the size, structure, focus, quality, and usefulness of documents makes Web documents much more heterogeneous than a typical electronic document collection. The wide variety of document types includes images, video, audio, and scripts, as well as many different document languages. Duplication of documents and sites is common. Documents are interconnected through networks of hyperlinks. Because of the size and dynamic nature of the Web, preprocessing all documents requires considerable resources and is often not feasible, certainly not an the frequent basis required to ensure currency. Query length is usually much shorter than in other environments-only a few words-and user behavior differs from that in other environments. These differences make the Web a novel environment for information retrieval (Baeza-Yates & Ribeiro-Neto, 1999b; Bharat & Henzinger, 1998; Huang, 2000).

Source

Annual review of information science and technology. 37(2003), S.91-126

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Abstract

The Indiana University School of Library and Information Science opened a new research laboratory in January 2003; The Indiana University School of Library and Information Science Information Processing Laboratory [IU IP Lab]. The purpose of the new laboratory is to facilitate collaboration between scientists in the department in the areas of information retrieval (IR) and information visualization (IV) research. The lab has several areas of focus. These include grid and cluster computing, and a standard Java-based software platform to support plug and play research datasets, a selection of standard IR modules and standard IV algorithms. Future development includes software to enable researchers to contribute datasets, IR algorithms, and visualization algorithms into the standard environment. We decided early on to use OAI-PMH as a resource discovery tool because it is consistent with our mission.

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Abstract

Over the past few years, temporal information processing and temporal database management have increasingly become hot topics. Nevertheless, only a few researchers have investigated these areas in the Chinese language. This lays down the objective of our research: to exploit Chinese language processing techniques for temporal information extraction and concept reasoning. In this article, we first study the mechanism for expressing time in Chinese. On the basis of the study, we then design a general frame structure for maintaining the extracted temporal concepts and propose a system for extracting time-dependent information from Hong Kong financial news. In the system, temporal knowledge is represented by different types of temporal concepts (TTC) and different temporal relations, including absolute and relative relations, which are used to correlate between action times and reference times. In analyzing a sentence, the algorithm first determines the situation related to the verb. This in turn will identify the type of temporal concept associated with the verb. After that, the relevant temporal information is extracted and the temporal relations are derived. These relations link relevant concept frames together in chronological order, which in turn provide the knowledge to fulfill users' queries, e.g., for question-answering (i.e., Q&A) applications

Source

Journal of the American Society for Information Science and technology. 52(2001) no.9, S.748-762

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Source

Information processing and management. 37(2001) no.2, S.231-254

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Imprint

Potsdam : Fachhochschule, Institut für Information und Dokumentation

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Abstract

While a number of researchers had experimented during the 1950's on automatic indexing and retrieval in various forms, it was Gerard Salton who brought the information retrieval experimental paradigm to full fruition, with his "SMART" system. His work has been enormously influential.

Source

Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates

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Abstract

Die vorliegende Arbeit beschäftigt sich mit modernen Retrievalverfahren in klassischen bibliotheksbezogenen Anwendungen. Wie die Verbindung der beiden gegensätzlich scheinenden Wortgruppen im Titel zeigt, werden in der Arbeit Aspekte aus der Informatik bzw. Informationswissenschaft mit Aspekten aus der Bibliothekstradition verknüpft. Nach einer kurzen Schilderung der Ausgangslage, der so genannten Informationsflut, im ersten Kapitel stellt das zweite Kapitel eine Einführung in die Theorie des Information Retrieval dar. Im Einzelnen geht es um die Grundlagen von Information Retrieval und Information-Retrieval-Systemen sowie um die verschiedenen Möglichkeiten der Informationserschließung. Hier werden Formal- und Sacherschließung, Indexierung und automatische Indexierung behandelt. Des Weiteren werden im Rahmen der Theorie des Information Retrieval unterschiedliche Information-Retrieval-Modelle und die Evaluation durch Retrievaltests vorgestellt. Nach der Theorie folgt im dritten Kapitel die Praxis des Information Retrieval. Es werden die organisationsinterne Anwendung, die Anwendung im Informations- und Dokumentationsbereich sowie die Anwendung im Bibliotheksbereich unterschieden. Die organisationsinterne Anwendung wird durch das Beispiel der Datenbank KURS zur Aus- und Weiterbildung veranschaulicht. Die Anwendung im Bibliotheksbereich bezieht sich in erster Linie auf den OPAC als Kompromiss zwischen bibliothekarischer Indexierung und Endnutzeranforderungen und auf seine Anreicherung (sog. Catalogue Enrichment), um das Retrieval zu verbessern. Der Bibliotheksbereich wird ausführlicher behandelt, indem ein Rückblick auf abgeschlossene Projekte zu Informations- und Indexierungssystemen aus den Neunziger Jahren (OSIRIS, MILOS I und II, KASCADE) sowie ein Einblick in aktuelle Projekte gegeben werden. In den beiden folgenden Kapiteln wird je ein aktuelles Projekt zur Verbesserung des Retrievals durch Kataloganreicherung, automatische Erschließung und fortschrittliche Retrievalverfahren präsentiert: das Suchportal dandelon.com und das 180T-Projekt des Hochschulbibliothekszentrums des Landes Nordrhein-Westfalen. Hierbei werden jeweils Projektziel, Projektpartner, Projektorganisation, Projektverlauf und die verwendete Technologie vorgestellt. Die Projekte unterscheiden sich insofern, dass in dem einen Fall eine große Verbundzentrale die Projektkoordination übernimmt, im anderen Fall jede einzelne teilnehmende Bibliothek selbst für die Durchführung verantwortlich ist. Im sechsten und letzten Kapitel geht es um das Fazit und die Perspektiven. Es werden sowohl die beiden beschriebenen Projekte bewertet als auch ein Ausblick auf Entwicklungen bezüglich des Bibliothekskatalogs gegeben. Diese Veröffentlichung geht zurück auf eine Master-Arbeit im postgradualen Fernstudiengang Master of Arts (Library and Information Science) an der Humboldt-Universität zu Berlin.

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Abstract

This work addresses the information retrieval problem of auto-indexing Arabic documents. Auto-indexing a text document refers to automatically extracting words that are suitable for building an index for the document. In this paper, we propose an auto-indexing method for Arabic text documents. This method is mainly based on morphological analysis and on a technique for assigning weights to words. The morphological analysis uses a number of grammatical rules to extract stem words that become candidate index words. The weight assignment technique computes weights for these words relative to the container document. The weight is based on how spread is the word in a document and not only on its rate of occurrence. The candidate index words are then sorted in descending order by weight so that information retrievers can select the more important index words. We empirically verify the usefulness of our method using several examples. For these examples, we obtained an average recall of 46% and an average precision of 64%.

Source

Information processing and management. 44(2008) no.4, S.1538-1545

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Abstract

Statistical association measures have been widely applied in information retrieval research, usually employing a clustering of documents or terms on the basis of their relationships. Applications of the association measures for term clustering include automatic thesaurus construction and query expansion. This research evaluates the similarity of six association measures by comparing the relationship and behavior they demonstrate in various analyses of a test corpus. Analysis techniques include comparisons of highly ranked term pairs and term clusters, analyses of the correlation among the association measures using Pearson's correlation coefficient and MDS mapping, and an analysis of the impact of a term frequency on the association values by means of z-score. The major findings of the study are as follows: First, the most similar association measures are mutual information and Yule's coefficient of colligation Y, whereas cosine and Jaccard coefficients, as well as X**2 statistic and likelihood ratio, demonstrate quite similar behavior for terms with high frequency. Second, among all the measures, the X**2 statistic is the least affected by the frequency of terms. Third, although cosine and Jaccard coefficients tend to emphasize high frequency terms, mutual information and Yule's Y seem to overestimate rare terms

Source

Journal of the American Society for Information Science and technology. 52(2001) no.4, S.283-296

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Information processing and management. 37(2001) no.2, S.255-277

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Source

Information - Wissenschaft und Praxis. 59(2008) H.5, S.285-292

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Source

Auf dem Weg zur Informationskultur: Wa(h)re Information? Festschrift für Norbert Henrichs zum 65. Geburtstag, Hrsg.: T.A. Schröder

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Abstract

We use a probabilistic mixture decomposition method to determine topics in the Pennsylvania Gazette, a major colonial U.S. newspaper from 1728-1800. We assess the value of several topic decomposition techniques for historical research and compare the accuracy and efficacy of various methods. After determining the topics covered by the 80,000 articles and advertisements in the entire 18th century run of the Gazette, we calculate how the prevalence of those topics changed over time, and give historically relevant examples of our findings. This approach reveals important information about the content of this colonial newspaper, and suggests the value of such approaches to a more complete understanding of early American print culture and society.

Source

Journal of the American Society for Information Science and Technology. 57(2006) no.6, S.753-767

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Abstract

Diese Diplomarbeit handelt von der Indexierung von unstrukturierten und natürlichsprachigen Dokumenten. Die zunehmende Informationsflut und die Zahl an veröffentlichten wissenschaftlichen Berichten und Büchern machen eine maschinelle inhaltliche Erschließung notwendig. Um die Anforderungen hierfür besser zu verstehen, werden Probleme der natürlichsprachigen schriftlichen Kommunikation untersucht. Die manuellen Techniken der Indexierung und die Dokumentationssprachen werden vorgestellt. Die Indexierung wird thematisch in den Bereich der inhaltlichen Erschließung und des Information Retrieval eingeordnet. Weiterhin werden Vor- und Nachteile von ausgesuchten Algorithmen untersucht und Softwareprodukte im Bereich des Information Retrieval auf ihre Arbeitsweise hin evaluiert. Anhand von Beispiel-Dokumenten werden die Ergebnisse einzelner Verfahren vorgestellt. Mithilfe des Projekts European Migration Network werden Probleme und grundlegende Anforderungen an die Durchführung einer inhaltlichen Erschließung identifiziert und Lösungsmöglichkeiten vorgeschlagen.

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Abstract

Automatic document categorization is an important research problem in Information Science and Natural Language Processing. Many applications, including, Word Sense Disambiguation and Information Retrieval in large collections, can benefit from such categorization. This paper focuses on automatic categorization of documents from the biomedical literature into broad discipline-based categories. Two different systems are described and contrasted: CISMeF, which uses rules based on human indexing of the documents by the Medical Subject Headings (MeSH) controlled vocabulary in order to assign metaterms (MTs), and Journal Descriptor Indexing (JDI), based on human categorization of about 4,000 journals and statistical associations between journal descriptors (JDs) and textwords in the documents. We evaluate and compare the performance of these systems against a gold standard of humanly assigned categories for 100 MEDLINE documents, using six measures selected from trec_eval. The results show that for five of the measures performance is comparable, and for one measure JDI is superior. We conclude that these results favor JDI, given the significantly greater intellectual overhead involved in human indexing and maintaining a rule base for mapping MeSH terms to MTs. We also note a JDI method that associates JDs with MeSH indexing rather than textwords, and it may be worthwhile to investigate whether this JDI method (statistical) and CISMeF (rule-based) might be combined and then evaluated showing they are complementary to one another.

Source

Journal of the American Society for Information Science and Technology. 60(2009) no.12, S.2530-2539