Search (104 results, page 1 of 6)

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Abstract

Propopses a Web-based architecture for searching distributed heterogeneous multi-asian language bibliographic sources, and describes a successful pilot implementation of the system at the Chinese Library (CLib) system developed in Singapore and tested at 2 university libraries and a public library

Date

1. 8.1996 22:08:06

Footnote

Contribution to a special issue devoted to the Proceedings of the 7th International World Wide Web Conference, held 14-18 April 1998, Brisbane, Australia

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Abstract

A lot of information that is already available on the Web, or retrieved from local information systems and social networks is structured in data silos that are not semantically related. Semantic technologies make it emerge that the use of typed links that directly express their relations are an advantage for every application that can reuse the incorporated knowledge about the data. For this reason, data integration, through reengineering (e.g. triplify), or querying (e.g. D2R) is an important task in order to make information available for everyone. Thus, in order to build a semantic map of the data, we need knowledge about data items itself and the relation between heterogeneous data items. In this paper, we present our work of providing Lexical Linked Data (LLD) through a meta-model that contains all the resources and gives the possibility to retrieve and navigate them from different perspectives. We combine the existing work done on knowledge domains (based on the Information Coding Classification) within the Multilingual Lexical Linked Data Cloud (based on the RDF/OWL EurowordNet and the related integrated lexical resources (MultiWordNet, EuroWordNet, MEMODATA Lexicon, Hamburg Methaphor DB).

Date

22. 9.2014 19:01:18

Source

Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik

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Abstract

This paper reports on the second part of an initiative of the authors on researching classification systems with the conceptual model defined by the Functional Requirements for Subject Authority Data (FRSAD) final report. In an earlier study, the authors explored whether the FRSAD conceptual model could be extended beyond subject authority data to model classification data. The focus of the current study is to determine if classification data modeled using FRSAD can be used to solve real-world discovery problems in multicultural and multilingual contexts. The paper discusses the relationships between entities (same type or different types) in the context of classification systems that involve multiple translations and /or multicultural implementations. Results of two case studies are presented in detail: (a) two instances of the DDC (DDC 22 in English, and the Swedish-English mixed translation of DDC 22), and (b) Chinese Library Classification. The use cases of conceptual models in practice are also discussed.

Source

Beyond libraries - subject metadata in the digital environment and semantic web. IFLA Satellite Post-Conference, 17-18 August 2012, Tallinn

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Abstract

Sehr viele Informationen sind bereits im Web verfügbar oder können aus isolierten strukturierten Datenspeichern wie Informationssystemen und sozialen Netzwerken gewonnen werden. Datenintegration durch Nachbearbeitung oder durch Suchmechanismen (z. B. D2R) ist deshalb wichtig, um Informationen allgemein verwendbar zu machen. Semantische Technologien ermöglichen die Verwendung definierter Verbindungen (typisierter Links), durch die ihre Beziehungen zueinander festgehalten werden, was Vorteile für jede Anwendung bietet, die das in Daten enthaltene Wissen wieder verwenden kann. Um ­eine semantische Daten-Landkarte herzustellen, benötigen wir Wissen über die einzelnen Daten und ihre Beziehung zu anderen Daten. Dieser Beitrag stellt unsere Arbeit zur Benutzung von Lexical Linked Data (LLD) durch ein Meta-Modell vor, das alle Ressourcen enthält und zudem die Möglichkeit bietet sie unter unterschiedlichen Gesichtspunkten aufzufinden. Wir verbinden damit bestehende Arbeiten über Wissensgebiete (basierend auf der Information Coding Classification) mit der Multilingual Lexical Linked Data Cloud (basierend auf der RDF/OWL-Repräsentation von EuroWordNet und den ähnlichen integrierten lexikalischen Ressourcen MultiWordNet, MEMODATA und die Hamburg Metapher DB).

Date

22. 9.2014 19:00:13

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Abstract

This article reports on the second part of an initiative of the authors on researching classification systems with the conceptual model defined by the Functional Requirements for Subject Authority Data (FRSAD) final report. In an earlier study, the authors explored whether the FRSAD conceptual model could be extended beyond subject authority data to model classification data. The focus of the current study is to determine if classification data modeled using FRSAD can be used to solve real-world discovery problems in multicultural and multilingual contexts. The article discusses the relationships between entities (same type or different types) in the context of classification systems that involve multiple translations and/or multicultural implementations. Results of two case studies are presented in detail: (a) two instances of the Dewey Decimal Classification [DDC] (DDC 22 in English, and the Swedish-English mixed translation of DDC 22), and (b) Chinese Library Classification. The use cases of conceptual models in practice are also discussed.

Footnote

Contribution in a special issue "Beyond libraries: Subject metadata in the digital environment and Semantic Web" - Enthält Beiträge der gleichnamigen IFLA Satellite Post-Conference, 17-18 August 2012, Tallinn.

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Abstract

Two probabilistic approaches to cross-lingual retrieval are in wide use today, those based on probabilistic models of relevance, as exemplified by INQUERY, and those based on language modeling. INQUERY, as a query net model, allows the easy incorporation of query operators, including a synonym operator, which has proven to be extremely useful in cross-language information retrieval (CLIR), in an approach often called structured query translation. In contrast, language models incorporate translation probabilities into a unified framework. We compare the two approaches on Arabic and Spanish data sets, using two kinds of bilingual dictionaries--one derived from a conventional dictionary, and one derived from a parallel corpus. We find that structured query processing gives slightly better results when queries are not expanded. On the other hand, when queries are expanded, language modeling gives better results, but only when using a probabilistic dictionary derived from a parallel corpus. We pursue two additional issues inherent in the comparison of structured query processing with language modeling. The first concerns query expansion, and the second is the role of translation probabilities. We compare conventional expansion techniques (pseudo-relevance feedback) with relevance modeling, a new IR approach which fits into the formal framework of language modeling. We find that relevance modeling and pseudo-relevance feedback achieve comparable levels of retrieval and that good translation probabilities confer a small but significant advantage.

Date

26.12.2007 20:22:11

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Abstract

The strategic importance of the internet as a tool for penetrating global markets is increasingly being realized by UK-based SMEs (Small- Medium-sized Enterprises). This may be evidenced by the proliferation over the past few years of SME web sites promoting products and services, and more recently still by the growing number of SMEs offering facilities on their web sites for conducting business transactions online. In this paper, we report on an exploratory study considering the use being made of the world wide web by UK-based SMEs. The study is focussed on the strategies SMEs are employing to communicate via the web with an international client base. We investigate in particular the languages being used to present web content, considering specifically the extent to which English is being employed. Preliminary results obtained to date suggest that there is heavy reliance on the assumption that the language of the web is English. Based on the findings of our study, we discuss some of the performance and competition issues surrounding the use of foreign languages in business, and consider some of the possible barriers to SMEs creating multilingual web sites. We conclude by making some recommendations for SMEs endeavouring to establish a multilingual online presence, and note the strategic role to be played by web designers, IT consultants, business strategists, professional translators, and localization specialists to help achieve this presence effectively and professionally

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Abstract

This article describes a scalable system for searching heterogeneous multilingual collections on the World Wide Web. It details a markup language for describing the characteristics of a search engine and its interface, and a protocol for requesting word translations between languages.

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Abstract

A lot of information that is already available on the Web, or retrieved from local information systems and social networks, is structured in data silos that are not semantically related. Semantic technologies make it apparent that the use of typed links that directly express their relations are an advantage for every application that can reuse the incorporated knowledge about the data. For this reason, data integration, through reengineering (e.g., triplify) or querying (e.g., D2R), is an important task in order to make information available for everyone. Thus, in order to build a semantic map of the data, we need knowledge about data items itself and the relation between heterogeneous data items. Here we present our work of providing Lexical Linked Data (LLD) through a meta-model that contains all the resources and gives the possibility to retrieve and navigate them from different perspectives. After giving the definition of Lexical Linked Data, we describe the existing datasets we collected and the new datasets we included. Here we describe their format and show some use cases where we link lexical data, and show how to reuse and inference semantic data derived from lexical data. Different lexical resources (MultiWordNet, EuroWordNet, MEMODATA Lexicon, the Hamburg Methaphor Database) are connected to each other towards an Integrated Vocabulary for LLD that we evaluate and present.

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Abstract

As illustrated by the World Wide Web, the volume of information in languages other than English has grown significantly in recent years. This highlights the importance of multilingual corpora. Much effort has been devoted to the compilation of multilingual corpora for the purpose of cross-lingual information retrieval and machine translation. Existing parallel corpora mostly involve European languages, such as English-French and English-Spanish. There is still a lack of parallel corpora between European languages and Asian. languages. In the authors' previous work, an alignment method to identify one-to-one Chinese and English title pairs was developed to construct an English-Chinese parallel corpus that works automatically from the World Wide Web, and a 100% precision and 87% recall were obtained. Careful analysis of these results has helped the authors to understand how the alignment method can be improved. A conceptual analysis was conducted, which includes the analysis of conceptual equivalent and conceptual information alternation in the aligned and nonaligned English-Chinese title pairs that are obtained by the alignment method. The result of the analysis not only reflects the characteristics of parallel corpora, but also gives insight into the strengths and weaknesses of the alignment method. In particular, conceptual alternation, such as omission and addition, is found to have a significant impact on the performance of the alignment method.

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Abstract

Users' cross-lingual queries to a digital library system might be short and the query terms may not be included in a common translation dictionary (unknown terms). In this article, the authors investigate the feasibility of exploiting the Web as the multilingual corpus source to translate unknown query terms for cross-language information retrieval in digital libraries. They propose a Webbased term translation approach to determine effective translations for unknown query terms by mining bilingual search-result pages obtained from a real Web search engine. This approach can enhance the construction of a domain-specific bilingual lexicon and bring multilingual support to a digital library that only has monolingual document collections. Very promising results have been obtained in generating effective translation equivalents for many unknown terms, including proper nouns, technical terms, and Web query terms, and in assisting bilingual lexicon construction for a real digital library system.

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Content

This paper explores the feasibility of developing mixed translations of the Dewey Decimal Classification (DDC system in countries/language groups where English enjoys wide use in academic and social discourse. A mixed translation uses existing DDC data in the vernacular plus additional data from the English-language full edition of the DDC to form a single mixed edition. Two approaches to mixed translations using Norwegian/English and Swedish/English DDC data are described, along with the design of a pilot study to evaluate use of a mixed translation as a classifier's tool.

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Abstract

For historical and cultural reasons, English phrases, especially proper nouns and new words, frequently appear in Web pages written primarily in East Asian languages such as Chinese, Korean, and Japanese. Although such English terms and their equivalences in these East Asian languages refer to the same concept, they are often erroneously treated as independent index units in traditional Information Retrieval (IR). This paper describes the degree to which the problem arises in IR and proposes a novel technique to solve it. Our method first extracts English terms from native Web documents in an East Asian language, and then unifies the extracted terms and their equivalences in the native language as one index unit. For Cross-Language Information Retrieval (CLIR), one of the major hindrances to achieving retrieval performance at the level of Mono-Lingual Information Retrieval (MLIR) is the translation of terms in search queries which can not be found in a bilingual dictionary. The Web mining approach proposed in this paper for concept unification of terms in different languages can also be applied to solve this well-known challenge in CLIR. Experimental results based on NTCIR and KT-Set test collections show that the high translation precision of our approach greatly improves performance of both Mono-Lingual and Cross-Language Information Retrieval.

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Abstract

Wikipedia is characterized by its dense link structure and a large number of articles in different languages, which make it a notable Web corpus for knowledge extraction and mining, in particular for mining the multilingual associations. In this paper, motivated by a psychological theory of word meaning, we propose a graph-based approach to constructing a cross-language association dictionary (CLAD) from Wikipedia, which can be used in a variety of cross-language accessing and processing applications. In order to evaluate the quality of the mined CLAD, and to demonstrate how the mined CLAD can be used in practice, we explore two different applications of the mined CLAD to cross-language information retrieval (CLIR). First, we use the mined CLAD to conduct cross-language query expansion; and, second, we use it to filter out translation candidates with low translation probabilities. Experimental results on a variety of standard CLIR test collections show that the CLIR retrieval performance can be substantially improved with the above two applications of CLAD, which indicates that the mined CLAD is of sound quality.

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Abstract

The information available in languages other than English on the World Wide Web and global information systems is increasing significantly. According to some recent reports. the growth of non-English speaking Internet users is significantly higher than the growth of English-speaking Internet users. Asia and Europe have become the two most-populated regions of Internet users. However, there are many different languages in the many different countries of Asia and Europe. And there are many countries in the world using more than one language as their official languages. For example, Chinese and English are official languages in Hong Kong SAR; English and French are official languages in Canada. In the global economy, information systems are no longer utilized by users in a single geographical region but all over the world. Information can be generated, stored, processed, and accessed in several different languages. All of this reveals the importance of research in multilingual information systems.

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Date

1. 2.2016 18:25:22

Source

Semantic keyword-based search on structured data sources: First COST Action IC1302 International KEYSTONE Conference, IKC 2015, Coimbra, Portugal, September 8-9, 2015. Revised Selected Papers. Eds.: J. Cardoso et al

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Abstract

Information retrieval systems' ability to retrieve highly relevant documents has become more and more important in the age of extremely large collections, such as the World Wide Web (WWW). The authors' aim was to find out how corpus-based cross-language information retrieval (CLIR) manages in retrieving highly relevant documents. They created a Finnish-Swedish comparable corpus from two loosely related document collections and used it as a source of knowledge for query translation. Finnish test queries were translated into Swedish and run against a Swedish test collection. Graded relevance assessments were used in evaluating the results and three relevance criterion levels-liberal, regular, and stringent-were applied. The runs were also evaluated with generalized recall and precision, which weight the retrieved documents according to their relevance level. The performance of the Comparable Corpus Translation system (COCOT) was compared to that of a dictionarybased query translation program; the two translation methods were also combined. The results indicate that corpus-based CUR performs particularly well with highly relevant documents. In average precision, COCOT even matched the monolingual baseline on the highest relevance level. The performance of the different query translation methods was further analyzed by finding out reasons for poor rankings of highly relevant documents.

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Abstract

While many websites aim at a large and linguistically diversified audience, they present their information mostly in the languages of larger speakers groups. Little is known about the effect on accessibility. We investigated the influence of a site's language offer on website access and search behaviour with two studies, and studied the interaction of language offers and domain knowledge. To achieve high ecological validity, we analysed data from a multilingual site's web-server logfile and from a questionnaire posted on it, and compared the behaviour of users who accessed the site in a non-native language to that of users who accessed it in their native language. Results from 277,809 user sessions and 165 international survey participants indicate that a website's languages may strongly reduce website access by users not supplied with information in their native language. Once inside a site, non-native speakers with high domain knowledge behave similarly to native speakers. However, non-native speakers' behaviour becomes language-sensitive when they have low domain knowledge.

Content

Beitrag in einem Themenheft "Minority languages, multimedia and the Web"

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Abstract

For the sake of national security, very large volumes of data and information are generated and gathered daily. Much of this data and information is written in different languages, stored in different locations, and may be seemingly unconnected. Crosslingual semantic interoperability is a major challenge to generate an overview of this disparate data and information so that it can be analyzed, shared, searched, and summarized. The recent terrorist attacks and the tragic events of September 11, 2001 have prompted increased attention an national security and criminal analysis. Many Asian countries and cities, such as Japan, Taiwan, and Singapore, have been advised that they may become the next targets of terrorist attacks. Semantic interoperability has been a focus in digital library research. Traditional information retrieval (IR) approaches normally require a document to share some common keywords with the query. Generating the associations for the related terms between the two term spaces of users and documents is an important issue. The problem can be viewed as the creation of a thesaurus. Apart from this, terrorists and criminals may communicate through letters, e-mails, and faxes in languages other than English. The translation ambiguity significantly exacerbates the retrieval problem. The problem is expanded to crosslingual semantic interoperability. In this paper, we focus an the English/Chinese crosslingual semantic interoperability problem. However, the developed techniques are not limited to English and Chinese languages but can be applied to many other languages. English and Chinese are popular languages in the Asian region. Much information about national security or crime is communicated in these languages. An efficient automatically generated thesaurus between these languages is important to crosslingual information retrieval between English and Chinese languages. To facilitate crosslingual information retrieval, a corpus-based approach uses the term co-occurrence statistics in parallel or comparable corpora to construct a statistical translation model to cross the language boundary. In this paper, the text based approach to align English/Chinese Hong Kong Police press release documents from the Web is first presented. We also introduce an algorithmic approach to generate a robust knowledge base based an statistical correlation analysis of the semantics (knowledge) embedded in the bilingual press release corpus. The research output consisted of a thesaurus-like, semantic network knowledge base, which can aid in semanticsbased crosslingual information management and retrieval.

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Abstract

Language barrier is the major problem that people face in searching for, retrieving, and understanding multilingual collections on the Internet. This paper deals with query translation and document translation in a Chinese-English information retrieval system called MTIR. Bilingual dictionary and monolingual corpus-based approaches are adopted to select suitable tranlated query terms. A machine transliteration algorithm is introduced to resolve proper name searching. We consider several design issues for document translation, including which material is translated, what roles the HTML tags play in translation, what the tradeoff is between the speed performance and the translation performance, and what from the translated result is presented in. About 100.000 Web pages translated in the last 4 months of 1997 are used for quantitative study of online and real-time Web page translation

Date

16. 2.2000 14:22:39