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Abstract

Eine der wesentlichen Aufgaben als Fachreferent*in ist die inhaltliche Erschließung der neuerworbenen Literatur, sowie die Begutachtung und Auswahl der neu erschienenen Werke in den jeweiligen Fachgebieten hinsichtlich der Relevanz für die eigenen Sammlungen gemäß dem Sammlungsprofil der TU Wien Bibliothek. Im Zuge der Corona-Krise wurde die herkömmliche Arbeitsweise in der Sacherschließung beeinträchtigt, und es haben sich neue Herausforderungen, aber auch Möglichkeiten ergeben. Neben der fehlenden Autopsie der Literatur leidet auch die Sichtung und Erwerbung neuer Literatur unter der physischen Abwesenheit vom Arbeitsplatz bzw. der entsprechenden technischen Infrastruktur. Auch der persönliche Austausch mit den Kolleg*innen wurde deutlich erschwert. Neben den Schwierigkeiten wurden aber auch die neuen Handlungsoptionen auf beruflicher und individueller Ebene positiv gesehen. In dem Artikel werden unsere individuellen Erfahrungen an der TU Wien Bibliothek sowie Ausblicke in die Zukunft wiedergegeben.

Footnote

https%3A%2F%2Fjournals.univie.ac.at%2Findex.php%2Fvoebm%2Farticle%2Fdownload%2F5332%2F5271%2F&usg=AOvVaw2yQdFGHlmOwVls7ANCpTii.

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Content

Vgl. unter: https://www.leibniz-science20.de%2Fforschung%2Fprojekte%2Faltmetrics-in-verschiedenen-wissenschaftsdisziplinen%2F&ei=2jTgVaaXGcK4Udj1qdgB&usg=AFQjCNFOPdONj4RKBDf9YDJOLuz3lkGYlg&sig2=5YI3KWIGxBmk5_kv0P_8iQ.

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Abstract

On a scientific concept hierarchy, a parent concept may have a few attributes, each of which has multiple values being a group of child concepts. We call these attributes facets: classification has a few facets such as application (e.g., face recognition), model (e.g., svm, knn), and metric (e.g., precision). In this work, we aim at building faceted concept hierarchies from scientific literature. Hierarchy construction methods heavily rely on hypernym detection, however, the faceted relations are parent-to-child links but the hypernym relation is a multi-hop, i.e., ancestor-to-descendent link with a specific facet "type-of". We use information extraction techniques to find synonyms, sibling concepts, and ancestor-descendent relations from a data science corpus. And we propose a hierarchy growth algorithm to infer the parent-child links from the three types of relationships. It resolves conflicts by maintaining the acyclic structure of a hierarchy.

Content

Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.

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Content

Folien eines Vortrages, 5. Kongress Bibliothek & Information Deutschland, Leipzig, 11.-14. März 2013.

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Abstract

Am 29. und 30. Oktober 2009 fand in der Königlichen Bibliothek in Den Haag das zweite internationale UDC-Seminar zum Thema "Classification at a Crossroad" statt. Organisiert wurde diese Konferenz - wie auch die erste Konferenz dieser Art im Jahr 2007 - vom UDC-Konsortium (UDCC). Im Mittelpunkt der diesjährigen Veranstaltung stand die Erschließung des World Wide Web unter besserer Nutzung von Klassifikationen (im Besonderen natürlich der UDC), einschließlich benutzerfreundlicher Repräsentationen von Informationen und Wissen. Standards, neue Technologien und Dienste, semantische Suche und der multilinguale Zugriff spielten ebenfalls eine Rolle. 135 Teilnehmer aus 35 Ländern waren dazu nach Den Haag gekommen. Das Programm umfasste mit 22 Vorträgen aus 14 verschiedenen Ländern eine breite Palette, wobei Großbritannien mit fünf Beiträgen am stärksten vertreten war. Die Tagesschwerpunkte wurden an beiden Konferenztagen durch die Eröffnungsvorträge gesetzt, die dann in insgesamt sechs thematischen Sitzungen weiter vertieft wurden.

Date

22. 1.2010 15:06:54

Theme

Klassifikationssysteme im Online-Retrieval

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Abstract

This paper maps the concepts "space" and "dimensionality" in classifications, in particular in visualizations hereof, from a historical perspective. After a historical excursion in the domain of classification theory of what in mathematics is known as dimensionality reduction in representations of a single universe of knowledge, its potentiality will be explored for information retrieval and navigation in the multiverse of the World Wide Web.

Date

22. 2.2013 11:31:25

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Abstract

Das Semantic Web ist die Vision einer Erweiterung des World Wide Webs, so dass die Daten nicht nur für Menschen leicht verständlich dargestellt werden, sondern auch von Maschinen verwertbar sind. Mit einer entsprechenden Ausgestaltung von Links zwischen einzelnen Webressourcen wäre das Web als riesige, globale Datenbank nutzbar. Darin könnten dann Softwareagenten für uns auch komplexe Fragestellungen und Planungen bearbeiten. In dieser Arbeit soll gezeigt werden, dass jede Bibliothek interessante Daten für das Semantic Web hat und umgekehrt von ihm profitieren kann. Ein Schwerpunkt liegt auf möglichen Anwendungsszenarien mit dem speziellen Fokus beim Bibliothekswesen.

Content

Vgl.: http://journals.ub.uni-heidelberg.de/index.php/bibliothek/article/view/9398.

Source

Perspektive Bibliothek. 1(2012) H.1, S.81-102

Theme

Semantic Web

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Abstract

The web has been, in the last decades, the place where information retrieval achieved its maximum importance, given its ubiquity and the sheer volume of information. However, its exponential growth made the retrieval task increasingly hard, relying in its effectiveness on idiosyncratic and somewhat biased ranking algorithms. To deal with this problem, a "new" web, called the Semantic Web (SW), was proposed, bringing along concepts like "Web of Data" and "Linked Data," although the definitions and connections among these concepts are often unclear. Based on a qualitative approach built over a literature review, a definition of SW is presented, discussing the related concepts sometimes used as synonyms. It concludes that the SW is a comprehensive and ambitious construct that includes the great purpose of making the web a global database. It also follows the specifications developed and/or associated with its operationalization and the necessary procedures for the connection of data in an open format on the web. The goals of this comprehensive SW are the union of two outcomes still tenuously connected: the virtually unlimited possibility of connections between data-the web domain-with the potentiality of the automated inference of "intelligent" systems-the semantic component.

Source

Journal of the Association for Information Science and Technology. 70(2019) no.7, S.701-714

Theme

Semantic Web

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Abstract

Exploiting context information in a web search engine helps fine-tuning web services and applications to deliver custom-made information to end users. While context, including user and environment information, cannot be exploited efficiently in the wired Internet interaction type, it is becoming accessible with the mobile web where users have an intimate relationship with their handsets. In this type of interaction, context plays a significant role enhancing information search and therefore, allowing a search engine to detect relevant content in all digital forms and formats. This chapter proposes a context model and an architecture that promote integration of context information for individuals and social communities to add value to their interaction with the mobile web. The architecture relies on efficient knowledge management of multimedia resources for a wide range of applications and web services. The research is illustrated with a corporate case study showing how efficient context integration improves usability of a mobile search engine.

Source

Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a

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Abstract

In this chapter, the authors describe the key indexing components of today's web search engines. As the World Wide Web has grown, the systems and methods for indexing have changed significantly. The authors present the data structures used, the features extracted, the infrastructure needed, and the options available for designing a brand new search engine. Techniques are highlighted that improve relevance of results, discuss trade-offs to best utilize machine resources, and cover distributed processing concepts in this context. In particular, the authors delve into the topics of indexing phrases instead of terms, storage in memory vs. on disk, and data partitioning. Some thoughts on information organization for the newly emerging data-forms conclude the chapter.

Source

Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a

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Abstract

Purpose - With an increase in the amount of multilingual content on the World Wide Web, users are often striving to access information provided in a language of which they are non-native speakers. The purpose of this paper is to present a comprehensive study of user profile representation techniques and investigate their use in personalized cross-language information retrieval (CLIR) systems through the means of personalized query expansion. Design/methodology/approach - The user profiles consist of weighted terms computed by using frequency-based methods such as tf-idf and BM25, as well as various latent semantic models trained on monolingual documents and cross-lingual comparable documents. This paper also proposes an automatic evaluation method for comparing various user profile generation techniques and query expansion methods. Findings - Experimental results suggest that latent semantic-weighted user profile representation techniques are superior to frequency-based methods, and are particularly suitable for users with a sufficient amount of historical data. The study also confirmed that user profiles represented by latent semantic models trained on a cross-lingual level gained better performance than the models trained on a monolingual level. Originality/value - Previous studies on personalized information retrieval systems have primarily investigated user profiles and personalization strategies on a monolingual level. The effect of utilizing such monolingual profiles for personalized CLIR remains unclear. The current study fills the gap by a comprehensive study of user profile representation for personalized CLIR and a novel personalized CLIR evaluation methodology to ensure repeatable and controlled experiments can be conducted.

Date

20. 1.2015 18:30:22

Source

Aslib journal of information management. 68(2016) no.4, S.448-477

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Abstract

Question Answering is an area of information retrieval with the added challenge of applying sophisticated techniques to identify the complex syntactic and semantic relationships present in text in order to provide a more sophisticated and satisfactory response to the user's information needs. For this reason, the authors see question answering as the next step beyond standard information retrieval. In this chapter state of the art question answering is covered focusing on providing an overview of systems, techniques and approaches that are likely to be employed in the next generations of search engines. Special attention is paid to question answering using the World Wide Web as the data source and to question answering exploiting the possibilities of Semantic Web. Considerations about the current issues and prospects for promising future research are also provided.

Source

Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a

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Abstract

Information Retrieval [IR] is the science of searching for documents, for information within documents, and for metadata about documents, as well as that of searching relational databases and the World Wide Web. This paper describes a document representation method instead of keywords ontological descriptors. The purpose of this paper is to propose a system for content-based querying of texts based on the availability of ontology for the concepts in the text domain and to develop new Indexing methods to improve RSV (Retrieval status value). There is a need for querying ontologies at various granularities to retrieve information from various sources to suit the requirements of Semantic web, to eradicate the mismatch between user request and response from the Information Retrieval system. Most of the search engines use indexes that are built at the syntactical level and return hits based on simple string comparisons. The indexes do not contain synonyms, cannot differentiate between homonyms and users receive different search results when they use different conjugation forms of the same word.

Series

Communications in computer and information science; vol.101

Source

Information and communication technologies: international conference; proceedings / ICT 2010, Kochi, Kerala, India, September 7 - 9, 2010. Ed.: V.V. Das

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Abstract

A user's query is considered to be an imprecise description of their information need. Automatic query expansion is the process of reformulating the original query with the goal of improving retrieval effectiveness. Many successful query expansion techniques model syntagmatic associations that infer two terms co-occur more often than by chance in natural language. However, structural linguistics relies on both syntagmatic and paradigmatic associations to deduce the meaning of a word. Given the success of dependency-based approaches to query expansion and the reliance on word meanings in the query formulation process, we argue that modeling both syntagmatic and paradigmatic information in the query expansion process improves retrieval effectiveness. This article develops and evaluates a new query expansion technique that is based on a formal, corpus-based model of word meaning that models syntagmatic and paradigmatic associations. We demonstrate that when sufficient statistical information exists, as in the case of longer queries, including paradigmatic information alone provides significant improvements in retrieval effectiveness across a wide variety of data sets. More generally, when our new query expansion approach is applied to large-scale web retrieval it demonstrates significant improvements in retrieval effectiveness over a strong baseline system, based on a commercial search engine.

Source

Journal of the Association for Information Science and Technology. 65(2014) no.8, S.1577-1596

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

The large volumes of medical information available on the web may provide answers for a wide range of users attempting to solve health-related problems. While experts generally utilize reliable resources for diagnosis search and professional development, novices utilize different (social) web resources to obtain information that helps them manage their health or the health of people who they care for. A diverse number of related search topics address clinical diagnosis, advice searching, information sharing, connecting with experts, etc. This paper focuses on the extent to which expertise can impact clinical query formulation, document relevance assessment and retrieval performance in the context of tailoring retrieval models and systems to experts vs. non-experts. The results show that medical domain expertise 1) plays an important role in the lexical representations of information needs; 2) significantly influences the perception of relevance even among users with similar levels of expertise and 3) reinforces the idea that a single ground truth does not exist, thereby leading to the variability of system rankings with respect to the level of user's expertise. The findings of this study presents opportunities for the design of personalized health-related IR systems, but also for providing insights about the evaluation of such systems.

Source

Information processing and management. 53(2017) no.2, S.332-350

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Source

Interactive information seeking, behaviour and retrieval. Eds.: Ruthven, I. u. D. Kelly

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Abstract

Currently, techniques for content description and query processing in Information Retrieval (IR) are based on keywords, and therefore provide limited capabilities to capture the conceptualizations associated with user needs and contents. Aiming to solve the limitations of keyword-based models, the idea of conceptual search, understood as searching by meanings rather than literal strings, has been the focus of a wide body of research in the IR field. More recently, it has been used as a prototypical scenario (or even envisioned as a potential "killer app") in the Semantic Web (SW) vision, since its emergence in the late nineties. However, current approaches to semantic search developed in the SW area have not yet taken full advantage of the acquired knowledge, accumulated experience, and technological sophistication achieved through several decades of work in the IR field. Starting from this position, this work investigates the definition of an ontology-based IR model, oriented to the exploitation of domain Knowledge Bases to support semantic search capabilities in large document repositories, stressing on the one hand the use of fully fledged ontologies in the semantic-based perspective, and on the other hand the consideration of unstructured content as the target search space. The major contribution of this work is an innovative, comprehensive semantic search model, which extends the classic IR model, addresses the challenges of the massive and heterogeneous Web environment, and integrates the benefits of both keyword and semantic-based search. Additional contributions include: an innovative rank fusion technique that minimizes the undesired effects of knowledge sparseness on the yet juvenile SW, and the creation of a large-scale evaluation benchmark, based on TREC IR evaluation standards, which allows a rigorous comparison between IR and SW approaches. Conducted experiments show that our semantic search model obtained comparable and better performance results (in terms of MAP and P@10 values) than the best TREC automatic system.

Source

Web semantics: science, services and agents on the World Wide Web. 9(2011) no.4, S.434-452

Theme

Semantic Web

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Abstract

Although technology can often correct spelling errors, the complex tasks of information searching and retrieval in an online public access catalog (OPAC) are made more difficult by these errors in users' input and bibliographic records. This study examines the search behaviors of 38 university students, divided into groups with either easy-to-spell or difficult-to-spell search terms, who were asked to find items in the OPAC with these search terms. Search behaviors and strategy use in the OPAC and on the World Wide Web (WWW) were examined. In general, students used familiar Web resources to check their spelling or discover more about the assigned topic. Students with difficult-to-spell search terms checked spelling more often, changed search strategies to look for the general topic and had fewer successful searches. Students unable to find the correct spelling of a search term were unable to complete their search. Students tended to search the OPAC as they would search a search engine, with few search terms or complex search strategies. The results of this study have implications for spell checking, user-focused OPAC design, and cataloging. Students' search behaviors are discussed by expanding Thatcher's (2006) Information-Seeking Process and Tactics for the WWW model to include OPACs.

Source

Journal of the American Society for Information Science and Technology. 61(2010) no.12, S.2461-2476

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Abstract

In this article, several procedures (e.g., measurements, information retrieval analyses, power law, association rules, hierarchical clustering) are introduced which were made on a pilot digital library. Information retrievals of web users from 01/01/2003 to 01/01/2006 on the internal search engine of the pilot digital library have been analyzed. With the power law method of data processing, a constant information retrieval pattern has been established, stable over a longer period of time. After this, the data have been analyzed. On the basis of the accomplished measurements and analyses, a series of mental models of web users for global (educational) purposes have been developed (e.g., the metamodel of thought hierarchy of web users, the segmentation model of web users), and the users were profiled in four different groups (adventurers, observers, applicable, and know-alls). The article concludes with the construction of a new knowledge management solution called multidimensional rank thesaurus.

Date

13. 7.2011 14:47:22

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Abstract

Purpose - Ontologies are prone to wide semantic variability due to subjective points of view of their composers. The purpose of this paper is to propose a new approach for maximal unification of diverse ontologies for controversial domains by their relations. Design/methodology/approach - Effective matching or unification of multiple ontologies for a specific domain is crucial for the success of many semantic web applications, such as semantic information retrieval and organization, document tagging, summarization and search. To this end, numerous automatic and semi-automatic techniques were proposed in the past decade that attempt to identify similar entities, mostly classes, in diverse ontologies for similar domains. Apparently, matching individual entities cannot result in full integration of ontologies' semantics without matching their inter-relations with all other-related classes (and instances). However, semantic matching of ontological relations still constitutes a major research challenge. Therefore, in this paper the authors propose a new paradigm for assessment of maximal possible matching and unification of ontological relations. To this end, several unification rules for ontological relations were devised based on ontological reference rules, and lexical and textual entailment. These rules were semi-automatically implemented to extend a given ontology with semantically matching relations from another ontology for a similar domain. Then, the ontologies were unified through these similar pairs of relations. The authors observe that these rules can be also facilitated to reveal the contradictory relations in different ontologies. Findings - To assess the feasibility of the approach two experiments were conducted with different sets of multiple personal ontologies on controversial domains constructed by trained subjects. The results for about 50 distinct ontology pairs demonstrate a good potential of the methodology for increasing inter-ontology agreement. Furthermore, the authors show that the presented methodology can lead to a complete unification of multiple semantically heterogeneous ontologies. Research limitations/implications - This is a conceptual study that presents a new approach for semantic unification of ontologies by a devised set of rules along with the initial experimental evidence of its feasibility and effectiveness. However, this methodology has to be fully automatically implemented and tested on a larger dataset in future research. Practical implications - This result has implication for semantic search, since a richer ontology, comprised of multiple aspects and viewpoints of the domain of knowledge, enhances discoverability and improves search results. Originality/value - To the best of the knowledge, this is the first study to examine and assess the maximal level of semantic relation-based ontology unification.

Date

20. 1.2015 18:30:22

Source

Aslib journal of information management. 66(2014) no.5, S.494-518

Theme

Semantic Web