Search (230 results, page 12 of 12)

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Abstract

Der Beitrag soll zeigen, welche fortgeschrittenen bibliometrischen und szientometrischen Daten für ein bewährtes Sample von 104 österreichischen Politikwissenschaftler*innen und 51 transnationalen Verlagsunternehmen enge statistische Beziehungen zwischen Indikatoren der Präsenz von Wissenschaftler*innen und transnationalen Verlagsunternehmen in den akademischen Lehrveranstaltungen der Welt (Classroom Citation, gemessen mit Open Syllabus) und anderen, herkömmlicheren bibliometrischen und szientometrischen Indikatoren (Libcitation gemessen mit dem OCLC Worldcat, sowie der H-Index der Zitierung in den vom System Scopus erfassten Fachzeitschriften der Welt bzw. dem Book Citation Index) bestehen. Die statistischen Berechnungen zeigen, basierend auf den Faktorenanalysen, die engen statistischen Beziehungen zwischen diesen Dimensionen. Diese Ergebnisse sind insbesondere in den Tabellen 5 und 9 dieser Arbeit (Komponentenkorrelationen) ableitbar.

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Abstract

Purpose A number of approaches and algorithms have been proposed over the years as a basis for automatic indexing. Many of these approaches suffer from precision inefficiency at low recall. The choice of indexing units has a great impact on search system effectiveness. The authors dive beyond simple terms indexing to propose a framework for multi-word terms (MWT) filtering and indexing. Design/methodology/approach In this paper, the authors rely on ranking MWT to filter them, keeping the most effective ones for the indexing process. The proposed model is based on filtering MWT according to their ability to capture the document topic and distinguish between different documents from the same collection. The authors rely on the hypothesis that the best MWT are those that achieve the greatest association degree. The experiments are carried out with English and French languages data sets. Findings The results indicate that this approach achieved precision enhancements at low recall, and it performed better than more advanced models based on terms dependencies. Originality/value Using and testing different association measures to select MWT that best describe the documents to enhance the precision in the first retrieved documents.

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Abstract

The purpose of this study is to provide a systematic literature review on taxonomy alignment methods in information science to explore the common research pipeline and characteristics. Design/methodology/approach The authors implement a five-step systematic literature review process relating to taxonomy alignment. They take on a knowledge organization system (KOS) perspective, and specifically examining the level of KOS on "taxonomies." Findings They synthesize the matching dimensions of 28 taxonomy alignment studies in terms of the taxonomy input, approach and output. In the input dimension, they develop three characteristics: tree shapes, variable names and symmetry; for approach: methodology, unit of matching, comparison type and relation type; for output: the number of merged solutions and whether original taxonomies are preserved in the solutions. Research limitations/implications The main research implications of this study are threefold: (1) to enhance the understanding of the characteristics of a taxonomy alignment work; (2) to provide a novel categorization of taxonomy alignment approaches into natural language processing approach, logic-based approach and heuristic-based approach; (3) to provide a methodological guideline on the must-include characteristics for future taxonomy alignment research. Originality/value There is no existing comprehensive review on the alignment of "taxonomies". Further, no other mapping survey research has discussed the comparison from a KOS perspective. Using a KOS lens is critical in understanding the broader picture of what other similar systems of organizations are, and enables us to define taxonomies more precisely.

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Abstract

The objective of this work is to discuss how vocabularies can contribute to assigning computational semantics to digital research data within the context of Big Data, so that computers can process them, allowing their reuse on large scale. A conceptualization of data is developed in an attempt to make it clearer what would be data, as an essential element of the Big Data phenomenon, and in particular, digital research data. It then proceeds to analyse digital research data uses and cases and their relation to semantics and vocabularies. Data is conceptualized as an artificial, intentional construction that represents a property of an entity within a specific domain and serves as the essential component of Big Data. The concept of semantic expressivity is discussed, and is used to classify the different vocabularies; within such a classification ontologies, are shown to be a type of knowledge organization system with a higher degree of semantic expressivity. Features of vocabularies that may be used within the context of the Semantic Web and the Linked Open Data to assign machine-processable semantics to Big Data are suggested. It is shown that semantics may be assigned at different data aggregation levels.

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Abstract

Training in knowl­edge organization (KO) involves an understanding of theories for the construction, maintenance, use, and evaluation of logical documentary languages. Teaching these KO concepts in LIS programs are related basically to accessing documents and retrieving their intellectual content. This study focuses on access to documents and exploring the ethical theme in all its dimensions as applied to the teaching of an undergraduate discipline as part of a Bachelor of Library Science degree offered at the Federal University of Minas Gerais (UFMG). As a methodology, a Project-based Pedagogy strategy is used in the teaching of a discipline called "Classification Systems: UDC" for students to classify a documentary resource from a collection on ethics. The teaching of bibliographic classification requires students to learn how to use the mechanisms available to form a notation as well as to use a syntax schema (tables) appropriately. Students also learn to determine a place for the document in the collection, considering the knowl­edge represented in the collection as a whole. Altogether, such a practice can help students to understand the theory underlying a classification system. The results show that the students were able to understand the basic concepts of knowl­edge organization. The students were also able to observe that the elements of the different tables of a classification tool are essential mechanisms for the organization of knowl­edge in other contexts, especially for specific purposes.

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Date

14. 1.2020 11:15:22

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Abstract

With the terrific growth of data volume and data being produced every second on millions of devices across the globe, there is a desperate need to manage the unstructured data available on web pages efficiently. Semantic Web or also known as Web of Trust structures the scattered data on the Internet according to the needs of the user. It is an extension of the World Wide Web (WWW) which focuses on manipulating web data on behalf of Humans. Due to the ability of the Semantic Web to integrate data from disparate sources and hence makes it more user-friendly, it is an emerging trend. Tim Berners-Lee first introduced the term Semantic Web and since then it has come a long way to become a more intelligent and intuitive web. Data Visualization plays an essential role in explaining complex concepts in a universal manner through pictorial representation, and the Semantic Web helps in broadening the potential of Data Visualization and thus making it an appropriate combination. The objective of this chapter is to provide fundamental insights concerning the semantic web technologies and in addition to that it also elucidates the issues as well as the solutions regarding the semantic web. The purpose of this chapter is to highlight the semantic web architecture in detail while also comparing it with the traditional search system. It classifies the semantic web architecture into three major pillars i.e. RDF, Ontology, and XML. Moreover, it describes different semantic web tools used in the framework and technology. It attempts to illustrate different approaches of the semantic web search engines. Besides stating numerous challenges faced by the semantic web it also illustrates the solutions.

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Abstract

This research explores current controversies within country dance communities and the implications of cultural and ethical issues related to representation of gender and race in a KOS for an ICH, while investigating the importance of context and the applicability of semantic approaches in the implementation of synonym rings. During development of a controlled vocabulary to represent dance concepts for country dance choreography, this study encountered and considered the importance of history and culture regarding synonymous and near-synonymous terms used to describe dance roles and choreographic elements. A subset of names for the same choreographic concepts across four subdomains of country dance (English country dance, Scottish country dance, contra dance, and modern western square dance) were used as a case study. These concepts included traditionally gendered dance roles and choreographic terms with a racially pejorative history. Through the lens of existing research on ethical knowl­edge organization, this study focused on principles and methods of transparency, multivocality, cultural warrant, cultural hospitality, and intersectionality to conduct a domain analysis of country dance resources. The analysis revealed differing levels of engagement and distinction among dance practitioners and communities for their preferences to use different terms for the same concept. Various lexical, grammatical, affective, social, political, and cultural aspects also emerged as important contextual factors for the use and assignment of terms. As a result, this study proposes the use of semantic annotation to represent those contextual factors and to allow mechanisms of user choice in the design of a country dance knowl­edge organization system. Future research arising from this study would focus on expanding examination to other country dance genres and continued exploration of the use of semantic approaches to represent contextual factors in controlled vocabulary development.

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Source

Frontiers in ecology and evolution, 22 October 2021 [https://www.frontiersin.org/articles/10.3389/fevo.2021.742639/full]

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Content

Kommentar Autor: "I would call GPT-3's answers not just clueless but cluelessly clueless, meaning that GPT-3 has no idea that it has no idea about what it is saying. There are no concepts behind the GPT-3 scenes; rather, there's just an unimaginably huge amount of absorbed text upon which it draws to produce answers. But since it had no input text about, say, dropping things onto the Andromeda galaxy (an idea that clearly makes no sense), the system just starts babbling randomly-but it has no sense that its random babbling is random babbling. Much the same could be said for how it reacts to the absurd notion of transporting Egypt (for the second time) across the Golden Gate Bridge, or the idea of mile-high vases."