Search (257 results, page 1 of 13)

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Abstract

Based on the salient features of the documents, automatic text summarization systems extract the key sentences from source documents. This process supports the users in evaluating the relevance of the extracted documents returned by information retrieval systems. Because of this tool, efficient filtering can be achieved. Indirectly, these systems help to resolve the problem of information overloading. Many automatic text summarization systems have been implemented for use with different languages. It has been established that the grammatical and lexical differences between languages have a significant effect on text processing. However, the impact of the language differences on the automatic text summarization systems has not yet been investigated. The authors provide an impact analysis of language difference on automatic text summarization. It includes the effect on the extraction processes, the scoring mechanisms, the performance, and the matching of the extracted sentences, using the parallel corpus in English and Chinese as the tested object. The analysis results provide a greater understanding of language differences and promote the future development of more advanced text summarization techniques.

Footnote

Beitrag einer special topic section on multilingual information systems

Source

Journal of the American Society for Information Science and Technology. 57(2006) no.5, S.684-696

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Abstract

Based on the premise that in a multilingual thesaurus all languages are equal, reviews the options and solutions offered by the guidelines to the developer of specialized thesauri. Introduces other problems of a sociocultural, and even of a truly political nature, which are a prominent features in the daily life of the thesaurus designer but with which the theory and the guidelines do not deal very well. Focuses in turn on semantic, managerial, and technological aspects of multilingual thesaurus construction, from the perspective of giving equal treatment to all languages involved

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Abstract

The Machine-Aided Indexing (MAI) program, developed by Access Innovations, Inc., is a semantic based, Boolean statement, rule interpreting application designed to operate in a multilingual environment. Use of MAI across several languages with controlled vocabularies for each language provides a consistency in indexing not available through any other mechanism

Source

Online information 92. Proc. of the 16th Int. Online Information Meeting, London, 8-10.12.1992. Ed. by David I. Raitt

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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.

Source

New review of hypermedia and multimedia. 11(2005) no.2, S.221-246

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Abstract

Purpose - The aim of the current paper is to test whether query translation is beneficial in web retrieval. Design/methodology/approach - The language pairs were Finnish-Swedish, English-German and Finnish-French. A total of 12-18 participants were recruited for each language pair. Each participant performed four retrieval tasks. The author's aim was to compare the performance of the translated queries with that of the target language queries. Thus, the author asked participants to formulate a source language query and a target language query for each task. The source language queries were translated into the target language utilizing a dictionary-based system. In English-German, also machine translation was utilized. The author used Google as the search engine. Findings - The results differed depending on the language pair. The author concluded that the dictionary coverage had an effect on the results. On average, the results of query-translation were better than in the traditional laboratory tests. Originality/value - This research shows that query translation in web is beneficial especially for users with moderate and non-active language skills. This is valuable information for developers of cross-language information retrieval systems.

Source

Journal of documentation. 64(2008) no.5, S.760-778

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Abstract

Purpose The purpose of this paper is threefold: to focus on the process of multilingual concept scheme construction and the challenges involved; to addresses concrete challenges faced in the construction process and especially those related to equivalence between terms and concepts; and to briefly outlines the translation strategies developed during the process of concept scheme construction. Design/methodology/approach The analysis is based on experience acquired during the establishment of the Finnish thesaurus and ontology service Finto as well as the trilingual General Finnish Ontology YSO, both of which are being maintained and further developed at the National Library of Finland. Findings Although uniform resource identifiers can be considered language-independent, they do not render concept schemes and their construction free of language-related challenges. The fundamental issue with all the challenges faced is how to maintain consistency and predictability when the nature of language requires each concept to be treated individually. The key to such challenges is to recognise the function of the vocabulary and the needs of its intended users. Social implications Open science increases the transparency of not only research products, but also metadata tools. Gaining a deeper understanding of the challenges involved in their construction is important for a great variety of users - e.g. indexers, vocabulary builders and information seekers. Today, multilingualism is an essential aspect at both the national and international information society level. Originality/value This paper draws on the practical challenges faced in concept scheme construction in a trilingual environment, with a focus on "concept scheme" as a translation and mapping unit.

Source

Journal of documentation. 73(2017) no.3, S.451-465

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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.

Source

Journal of the American Society for Information Science and Technology. 57(2006) no.5, S.629-631

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Abstract

Cross-language information retrieval (CLIR) systems allow users to find documents written in different languages from that of their query. Simple knowledge structures such as bilingual term lists have proven to be a remarkably useful basis for bridging that language gap. A broad array of dictionary-based techniques have demonstrated utility, but comparison across techniques has been difficult because evaluation results often span only a limited range of conditions. This article identifies the key issues in dictionary-based CLIR, develops unified frameworks for term selection and term translation that help to explain the relationships among existing techniques, and illustrates the effect of those techniques using four contrasting languages for systematic experiments with a uniform query translation architecture. Key results include identification of a previously unseen dependence of pre- and post-translation expansion on orthographic cognates and development of a query-specific measure for translation fanout that helps to explain the utility of structured query methods.

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Abstract

This article explores how best to use lexical and statistical translation evidence together for cross-language information retrieval (CLIR). Lexical translation evidence is assembled from Wikipedia and from a large machine-readable dictionary, statistical translation evidence is drawn from parallel corpora, and evidence from co-occurrence in the document language provides a basis for limiting the adverse effect of translation ambiguity. Coverage statistics for NII Testbeds and Community for Information Access Research (NTCIR) queries confirm that these resources have complementary strengths. Experiments with translation evidence from a small parallel corpus indicate that even rather rough estimates of translation probabilities can yield further improvements over a strong technique for translation weighting based on using Jensen-Shannon divergence as a term-association measure. Finally, a novel approach to posttranslation query expansion using a random walk over the Wikipedia concept link graph is shown to yield further improvements over alternative techniques for posttranslation query expansion. Evaluation results on the NTCIR-5 English-Korean test collection show statistically significant improvements over strong baselines.

Source

Journal of the Association for Information Science and Technology. 66(2015) no.1, S.23-39

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Abstract

The machine aided indexing (MAI) software devloped by Access Innovations, Inc., is a semantic based, Boolean statement, rule interpreting application with 3 modules: the MA engine which accepts input files, matches terms in the knowledge base, interprets rules, and outputs a text file with suggested indexing terms; a rule building application allowing each Boolean style rule in the knowledge base to be created or modifies; and a statistical computation module which analyzes performance of the MA software against text manually indexed by professional human indexers. The MA software can be applied across multiple languages and can be used where the text to be searched is in one language and the indexes to be output are in another

Source

Proceedings of the 14th National Online Meeting 1993, New York, 4-6 May 1993. Ed.: M.E. Williams

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Abstract

General graph random walk has been successfully applied in multi-document summarization, but it has some limitations to process documents by this way. In this paper, we propose a novel hypergraph based vertex-reinforced random walk framework for multi-document summarization. The framework first exploits the Hierarchical Dirichlet Process (HDP) topic model to learn a word-topic probability distribution in sentences. Then the hypergraph is used to capture both cluster relationship based on the word-topic probability distribution and pairwise similarity among sentences. Finally, a time-variant random walk algorithm for hypergraphs is developed to rank sentences which ensures sentence diversity by vertex-reinforcement in summaries. Experimental results on the public available dataset demonstrate the effectiveness of our framework.

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Abstract

Welcome to the very first issue of EuropeanaTech Insight, a multimedia publication about research and development within the EuropeanaTech community. EuropeanaTech is a very active community. It spans all of Europe and is made up of technical experts from the various disciplines within digital cultural heritage. At any given moment, members can be found presenting their work in project meetings, seminars and conferences around the world. Now, through EuropeanaTech Insight, we can share that inspiring work with the whole community. In our first three issues, we're showcasing topics discussed at the EuropeanaTech 2015 Conference, an exciting event that gave rise to lots of innovative ideas and fruitful conversations on the themes of data quality, data modelling, open data, data re-use, multilingualism and discovery. Welcome, bienvenue, bienvenido, Välkommen, Tervetuloa to the first Issue of EuropeanaTech Insight. Are we talking your language? No? Well I can guarantee you Europeana is. One of the European Union's great beauties and strengths is its diversity. That diversity is perhaps most evident in the 24 different languages spoken in the EU. Making it possible for all European citizens to easily and seamlessly communicate in their native language with others who do not speak that language is a huge technical undertaking. Translating documents, news, speeches and historical texts was once exclusively done manually. Clearly, that takes a huge amount of time and resources and means that not everything can be translated... However, with the advances in machine and automatic translation, it's becoming more possible to provide instant and pretty accurate translations. Europeana provides access to over 40 million digitised cultural heritage offering content in over 33 languages. But what value does Europeana provide if people can only find results in their native language? None. That's why the EuropeanaTech community is collectively working towards making it more possible for everyone to discover our collections in their native language. In this issue of EuropeanaTech Insight, we hear from community members who are making great strides in machine translation and enrichment tools to help improve not only access to data, but also how we retrieve, browse and understand it.

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Abstract

The quality of stemming algorithms is typically measured in two different ways: (i) how accurately they map the variant forms of a word to the same stem; or (ii) how much improvement they bring to Information Retrieval systems. In this article, we evaluate various stemming algorithms, in four languages, in terms of accuracy and in terms of their aid to Information Retrieval. The aim is to assess whether the most accurate stemmers are also the ones that bring the biggest gain in Information Retrieval. Experiments in English, French, Portuguese, and Spanish show that this is not always the case, as stemmers with higher error rates yield better retrieval quality. As a byproduct, we also identified the most accurate stemmers and the best for Information Retrieval purposes.

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Abstract

The role of linguistics in information access, extraction and dissemination is essential. Radical changes in the techniques of information and communication at the end of the twentieth century have had a significant effect on the function of the linguistic paradigm and its applications in all forms of communication. The introduction of new technical means have deeply changed the possibilities for the distribution of information. In this situation, what is the role of the linguistic paradigm and its practical applications, i.e., natural language processing (NLP) techniques when applied to information access? What solutions can linguistics offer in human computer interaction, extraction and management? Many fields show the relevance of the linguistic paradigm through the various technologies that require NLP, such as document and message understanding, information detection, extraction, and retrieval, question and answer, cross-language information retrieval (CLIR), text summarization, filtering, and spoken document retrieval. This paper focuses on the central role of human language technologies in the information society, surveys the current situation, describes the benefits of the above mentioned applications, outlines successes and challenges, and discusses solutions. It reviews the resources and means needed to advance information access and dissemination across language boundaries in the twenty-first century. Multilingualism, which is a natural result of globalization, requires more effort in the direction of language technology. The scope of human language technology (HLT) is large, so we limit our review to applications that involve multilinguality.

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Abstract

When we first began discussing with Peter Paulson, executive director of OCLC Forest Press, the possibility of translating into Spanish the twentieth edition of the Dewey Decimal Classification, and even during the initial contact we had with the late John A. Humphry, we knew that the project would be a complex and hard task. The reality was that the project exceeded all expectations and was much more complex and difficult than we had anticipated. This not only made it more interesting for those who participated in its development, but also made it an extraordinary challenge, especially due to the time frame initially foreseen for its development: eight to ten months. Once we agreed with Peter Paulson on the basic terms of the project, Rojas Eberhard Editores was able to convince Information Handling Services (a company located in Denver, Colorado, known worldwide for its products and services in the field of technological information) to participate with us in this translation and publication project. Information Handling Services channeled its participation through its subsidiary in Mexico, to facilitate the integration of the project into the main zone of influence of the final product: Latin America.

Source

Dewey Decimal Classification: Edition 21 and International perspectives: papers from a workshop presented at the General Conference of the International Deferation of Library Associations and Institutions (IFLA), Beijing, China, August 29, 1996. Ed.: L.M. Chan and J.S. Mitchell

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Abstract

Over the past 50 years, a variety of language-related capabilities has been developed in machine translation, information retrieval, speech recognition, text summarization, and so on. These applications rest upon a set of core techniques such as language modeling, information extraction, parsing, generation, and multimedia planning and integration; and they involve methods using statistics, rules, grammars, lexicons, ontologies, training techniques, and so on. It is a puzzling fact that although all of this work deals with language in some form or other, the major applications have each developed a separate research field. For example, there is no reason why speech recognition techniques involving n-grams and hidden Markov models could not have been used in machine translation 15 years earlier than they were, or why some of the lexical and semantic insights from the subarea called Computational Linguistics are still not used in information retrieval.
This picture will rapidly change. The twin challenges of massive information overload via the web and ubiquitous computers present us with an unavoidable task: developing techniques to handle multilingual and multi-modal information robustly and efficiently, with as high quality performance as possible. The most effective way for us to address such a mammoth task, and to ensure that our various techniques and applications fit together, is to start talking across the artificial research boundaries. Extending the current technologies will require integrating the various capabilities into multi-functional and multi-lingual natural language systems. However, at this time there is no clear vision of how these technologies could or should be assembled into a coherent framework. What would be involved in connecting a speech recognition system to an information retrieval engine, and then using machine translation and summarization software to process the retrieved text? How can traditional parsing and generation be enhanced with statistical techniques? What would be the effect of carefully crafted lexicons on traditional information retrieval? At which points should machine translation be interleaved within information retrieval systems to enable multilingual processing?

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Source

Knowledge organization for a sustainable world: challenges and perspectives for cultural, scientific, and technological sharing in a connected society : proceedings of the Fourteenth International ISKO Conference 27-29 September 2016, Rio de Janeiro, Brazil / organized by International Society for Knowledge Organization (ISKO), ISKO-Brazil, São Paulo State University ; edited by José Augusto Chaves Guimarães, Suellen Oliveira Milani, Vera Dodebei

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Abstract

Spanish is one of the most widely spoken languages in the world and a review of the lists of subject headings in this language reveals numerous efforts over a period of time, usually involving some form of collaboration, but largely isolated from each other. Technological developments suggest that a greater degree of cooperation is now possible and would be beneficial to the international library community if other barriers can be surmounted. The lcsh-es.org project demonstrates this concept in a practical way and suggest a new model for international cooperation in authority control. The site may be accessed at http://lcsh-es.org.

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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.

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Abstract

The architecture of multilingual software systems is sometimes centred around an intermediate language. The question is analyzed to what extent this approach can be useful for multilingual thesauri, in particular regarding the functionality the thesaurus is designed to fulfil. Both the runtime use, and the construction and maintenance of the system is taken into consideration. Using the perspective of general language technology enables to draw on experience from a broader range of fields beyond thesaurus design itself as well as to consider the possibility of using a thesaurus as a knowledge module in various systems which process natural language. Therefore the features which thesauri and other natural-language processing systems have in common are emphasized, especially at the level of systems design and their core functionality

Source

Knowledge organization. 22(1995) nos.3/4, S.136-140