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  1. Xiong, C.: Knowledge based text representations for information retrieval (2016) 0.23 
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    Abstract
    The successes of information retrieval (IR) in recent decades were built upon bag-of-words representations. Effective as it is, bag-of-words is only a shallow text understanding; there is a limited amount of information for document ranking in the word space. This dissertation goes beyond words and builds knowledge based text representations, which embed the external and carefully curated information from knowledge bases, and provide richer and structured evidence for more advanced information retrieval systems. This thesis research first builds query representations with entities associated with the query. Entities' descriptions are used by query expansion techniques that enrich the query with explanation terms. Then we present a general framework that represents a query with entities that appear in the query, are retrieved by the query, or frequently show up in the top retrieved documents. A latent space model is developed to jointly learn the connections from query to entities and the ranking of documents, modeling the external evidence from knowledge bases and internal ranking features cooperatively. To further improve the quality of relevant entities, a defining factor of our query representations, we introduce learning to rank to entity search and retrieve better entities from knowledge bases. In the document representation part, this thesis research also moves one step forward with a bag-of-entities model, in which documents are represented by their automatic entity annotations, and the ranking is performed in the entity space.
    This proposal includes plans to improve the quality of relevant entities with a co-learning framework that learns from both entity labels and document labels. We also plan to develop a hybrid ranking system that combines word based and entity based representations together with their uncertainties considered. At last, we plan to enrich the text representations with connections between entities. We propose several ways to infer entity graph representations for texts, and to rank documents using their structure representations. This dissertation overcomes the limitation of word based representations with external and carefully curated information from knowledge bases. We believe this thesis research is a solid start towards the new generation of intelligent, semantic, and structured information retrieval.
    Content
    Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.
    Imprint
    Pittsburgh, PA : Carnegie Mellon University, School of Computer Science, Language Technologies Institute
  2. Huo, W.: Automatic multi-word term extraction and its application to Web-page summarization (2012) 0.14 
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    Abstract
    In this thesis we propose three new word association measures for multi-word term extraction. We combine these association measures with LocalMaxs algorithm in our extraction model and compare the results of different multi-word term extraction methods. Our approach is language and domain independent and requires no training data. It can be applied to such tasks as text summarization, information retrieval, and document classification. We further explore the potential of using multi-word terms as an effective representation for general web-page summarization. We extract multi-word terms from human written summaries in a large collection of web-pages, and generate the summaries by aligning document words with these multi-word terms. Our system applies machine translation technology to learn the aligning process from a training set and focuses on selecting high quality multi-word terms from human written summaries to generate suitable results for web-page summarization.
    Content
    A Thesis presented to The University of Guelph In partial fulfilment of requirements for the degree of Master of Science in Computer Science. Vgl. Unter: http://www.inf.ufrgs.br%2F~ceramisch%2Fdownload_files%2Fpublications%2F2009%2Fp01.pdf.
    Date
    10. 1.2013 19:22:47
    Imprint
    Guelph, Ontario : University of Guelph
  3. Farazi, M.: Faceted lightweight ontologies : a formalization and some experiments (2010) 0.13 
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    Abstract
    While classifications are heavily used to categorize web content, the evolution of the web foresees a more formal structure - ontology - which can serve this purpose. Ontologies are core artifacts of the Semantic Web which enable machines to use inference rules to conduct automated reasoning on data. Lightweight ontologies bridge the gap between classifications and ontologies. A lightweight ontology (LO) is an ontology representing a backbone taxonomy where the concept of the child node is more specific than the concept of the parent node. Formal lightweight ontologies can be generated from their informal ones. The key applications of formal lightweight ontologies are document classification, semantic search, and data integration. However, these applications suffer from the following problems: the disambiguation accuracy of the state of the art NLP tools used in generating formal lightweight ontologies from their informal ones; the lack of background knowledge needed for the formal lightweight ontologies; and the limitation of ontology reuse. In this dissertation, we propose a novel solution to these problems in formal lightweight ontologies; namely, faceted lightweight ontology (FLO). FLO is a lightweight ontology in which terms, present in each node label, and their concepts, are available in the background knowledge (BK), which is organized as a set of facets. A facet can be defined as a distinctive property of the groups of concepts that can help in differentiating one group from another. Background knowledge can be defined as a subset of a knowledge base, such as WordNet, and often represents a specific domain.
    Content
    PhD Dissertation at International Doctorate School in Information and Communication Technology. Vgl.: https%3A%2F%2Fcore.ac.uk%2Fdownload%2Fpdf%2F150083013.pdf&usg=AOvVaw2n-qisNagpyT0lli_6QbAQ.
    Imprint
    Trento : University / Department of information engineering and computer science
  4. Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005) 0.13 
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    Abstract
    By the explosion of possibilities for a ubiquitous content production, the information overload problem reaches the level of complexity which cannot be managed by traditional modelling approaches anymore. Due to their pure syntactical nature traditional information retrieval approaches did not succeed in treating content itself (i.e. its meaning, and not its representation). This leads to a very low usefulness of the results of a retrieval process for a user's task at hand. In the last ten years ontologies have been emerged from an interesting conceptualisation paradigm to a very promising (semantic) modelling technology, especially in the context of the Semantic Web. From the information retrieval point of view, ontologies enable a machine-understandable form of content description, such that the retrieval process can be driven by the meaning of the content. However, the very ambiguous nature of the retrieval process in which a user, due to the unfamiliarity with the underlying repository and/or query syntax, just approximates his information need in a query, implies a necessity to include the user in the retrieval process more actively in order to close the gap between the meaning of the content and the meaning of a user's query (i.e. his information need). This thesis lays foundation for such an ontology-based interactive retrieval process, in which the retrieval system interacts with a user in order to conceptually interpret the meaning of his query, whereas the underlying domain ontology drives the conceptualisation process. In that way the retrieval process evolves from a query evaluation process into a highly interactive cooperation between a user and the retrieval system, in which the system tries to anticipate the user's information need and to deliver the relevant content proactively. Moreover, the notion of content relevance for a user's query evolves from a content dependent artefact to the multidimensional context-dependent structure, strongly influenced by the user's preferences. This cooperation process is realized as the so-called Librarian Agent Query Refinement Process. In order to clarify the impact of an ontology on the retrieval process (regarding its complexity and quality), a set of methods and tools for different levels of content and query formalisation is developed, ranging from pure ontology-based inferencing to keyword-based querying in which semantics automatically emerges from the results. Our evaluation studies have shown that the possibilities to conceptualize a user's information need in the right manner and to interpret the retrieval results accordingly are key issues for realizing much more meaningful information retrieval systems.
    Content
    Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.
  5. Kiren, T.: ¬A clustering based indexing technique of modularized ontologies for information retrieval (2017) 0.08 
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    Abstract
    Indexing plays a vital role in Information Retrieval. With the availability of huge volume of information, it has become necessary to index the information in such a way to make easier for the end users to find the information they want efficiently and accurately. Keyword-based indexing uses words as indexing terms. It is not capable of capturing the implicit relation among terms or the semantics of the words in the document. To eliminate this limitation, ontology-based indexing came into existence, which allows semantic based indexing to solve complex and indirect user queries. Ontologies are used for document indexing which allows semantic based information retrieval. Existing ontologies or the ones constructed from scratch are used presently for indexing. Constructing ontologies from scratch is a labor-intensive task and requires extensive domain knowledge whereas use of an existing ontology may leave some important concepts in documents un-annotated. Using multiple ontologies can overcome the problem of missing out concepts to a great extent, but it is difficult to manage (changes in ontologies over time by their developers) multiple ontologies and ontology heterogeneity also arises due to ontologies constructed by different ontology developers. One possible solution to managing multiple ontologies and build from scratch is to use modular ontologies for indexing.
    Modular ontologies are built in modular manner by combining modules from multiple relevant ontologies. Ontology heterogeneity also arises during modular ontology construction because multiple ontologies are being dealt with, during this process. Ontologies need to be aligned before using them for modular ontology construction. The existing approaches for ontology alignment compare all the concepts of each ontology to be aligned, hence not optimized in terms of time and search space utilization. A new indexing technique is proposed based on modular ontology. An efficient ontology alignment technique is proposed to solve the heterogeneity problem during the construction of modular ontology. Results are satisfactory as Precision and Recall are improved by (8%) and (10%) respectively. The value of Pearsons Correlation Coefficient for degree of similarity, time, search space requirement, precision and recall are close to 1 which shows that the results are significant. Further research can be carried out for using modular ontology based indexing technique for Multimedia Information Retrieval and Bio-Medical information retrieval.
    Content
    Submitted to the Faculty of the Computer Science and Engineering Department of the University of Engineering and Technology Lahore in partial fulfillment of the requirements for the Degree of Doctor of Philosophy in Computer Science (2009 - 009-PhD-CS-04). Vgl.: http://prr.hec.gov.pk/jspui/bitstream/123456789/8375/1/Taybah_Kiren_Computer_Science_HSR_2017_UET_Lahore_14.12.2017.pdf.
    Date
    20. 1.2015 18:30:22
    Imprint
    Lahore : University of Engineering and Technology / Department of Computer Science and Engineering
  6. Seidlmayer, E.: ¬An ontology of digital objects in philosophy : an approach for practical use in research (2018) 0.08 
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    Abstract
    The digitalization of research enables new scientific insights and methods, especially in the humanities. Nonetheless, electronic book editions, encyclopedias, mobile applications or web sites presenting research projects are not in broad use in academic philosophy. This is contradictory to the large amount of helpful tools facilitating research also bearing new scientific subjects and approaches. A possible solution to this dilemma is the systematization and promotion of these tools in order to improve their accessibility and fully exploit the potential of digitalization for philosophy.
  7. Slavic-Overfield, A.: Classification management and use in a networked environment : the case of the Universal Decimal Classification (2005) 0.07 
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    Abstract
    In the Internet information space, advanced information retrieval (IR) methods and automatic text processing are used in conjunction with traditional knowledge organization systems (KOS). New information technology provides a platform for better KOS publishing, exploitation and sharing both for human and machine use. Networked KOS services are now being planned and developed as powerful tools for resource discovery. They will enable automatic contextualisation, interpretation and query matching to different indexing languages. The Semantic Web promises to be an environment in which the quality of semantic relationships in bibliographic classification systems can be fully exploited. Their use in the networked environment is, however, limited by the fact that they are not prepared or made available for advanced machine processing. The UDC was chosen for this research because of its widespread use and its long-term presence in online information retrieval systems. It was also the first system to be used for the automatic classification of Internet resources, and the first to be made available as a classification tool on the Web. The objective of this research is to establish the advantages of using UDC for information retrieval in a networked environment, to highlight the problems of automation and classification exchange, and to offer possible solutions. The first research question was is there enough evidence of the use of classification on the Internet to justify further development with this particular environment in mind? The second question is what are the automation requirements for the full exploitation of UDC and its exchange? The third question is which areas are in need of improvement and what specific recommendations can be made for implementing the UDC in a networked environment? A summary of changes required in the management and development of the UDC to facilitate its full adaptation for future use is drawn from this analysis.
    Content
    Thesis submitted for the Degree of Doctor of Philosophy at the University of London
  8. Mao, M.: Ontology mapping : towards semantic interoperability in distributed and heterogeneous environments (2008) 0.05 
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    Abstract
    This dissertation studies ontology mapping: the problem of finding semantic correspondences between similar elements of different ontologies. In the dissertation, elements denote classes or properties of ontologies. The goal of this research is to use ontology mapping to make heterogeneous information more accessible. The World Wide Web (WWW) now is widely used as a universal medium for information exchange. Semantic interoperability among different information systems in the WWW is limited due to information heterogeneity, and the non semantic nature of HTML and URLs. Ontologies have been suggested as a way to solve the problem of information heterogeneity by providing formal, explicit definitions of data and reasoning ability over related concepts. Given that no universal ontology exists for the WWW, work has focused on finding semantic correspondences between similar elements of different ontologies, i.e., ontology mapping. Ontology mapping can be done either by hand or using automated tools. Manual mapping becomes impractical as the size and complexity of ontologies increases. Full or semi-automated mapping approaches have been examined by several research studies. Previous full or semiautomated mapping approaches include analyzing linguistic information of elements in ontologies, treating ontologies as structural graphs, applying heuristic rules and machine learning techniques, and using probabilistic and reasoning methods etc. In this paper, two generic ontology mapping approaches are proposed. One is the PRIOR+ approach, which utilizes both information retrieval and artificial intelligence techniques in the context of ontology mapping. The other is the non-instance learning based approach, which experimentally explores machine learning algorithms to solve ontology mapping problem without requesting any instance. The results of the PRIOR+ on different tests at OAEI ontology matching campaign 2007 are encouraging. The non-instance learning based approach has shown potential for solving ontology mapping problem on OAEI benchmark tests.
    Content
    Submitted to the Graduate Faculty of School of Information Sciences in partial fulfillment of the requirements for the degree of Doctor of Philosophy.
    Imprint
    Pittsburgh : University of Pittsburgh
  9. Kirk, J.: Theorising information use : managers and their work (2002) 0.05 
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    Abstract
    The focus of this thesis is information use. Although a key concept in information behaviour, information use has received little attention from information science researchers. Studies of other key concepts such as information need and information seeking are dominant in information behaviour research. Information use is an area of interest to information professionals who rely on research outcomes to shape their practice. There are few empirical studies of how people actually use information that might guide and refine the development of information systems, products and services.
    Content
    A thesis submitted to the University of Technology, Sydney in fulfilment of the requirements for the degree of Doctor of Philosophy. - Vgl. unter: http://epress.lib.uts.edu.au/dspace/bitstream/2100/309/2/02whole.pdf.
    Imprint
    Sydney : University of Technology / Faculty of Humanities and Social Sciences
  10. Noy, N.F.: Knowledge representation for intelligent information retrieval in experimental sciences (1997) 0.05 
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    Abstract
    More and more information is available on-line every day. The greater the amount of on-line information, the greater the demand for tools that process and disseminate this information. Processing electronic information in the form of text and answering users' queries about that information intelligently is one of the great challenges in natural language processing and information retrieval. The research presented in this talk is centered on the latter of these two tasks: intelligent information retrieval. In order for information to be retrieved, it first needs to be formalized in a database or knowledge base. The ontology for this formalization and assumptions it is based on are crucial to successful intelligent information retrieval. We have concentrated our effort on developing an ontology for representing knowledge in the domains of experimental sciences, molecular biology in particular. We show that existing ontological models cannot be readily applied to represent this domain adequately. For example, the fundamental notion of ontology design that every "real" object is defined as an instance of a category seems incompatible with the universe where objects can change their category as a result of experimental procedures. Another important problem is representing complex structures such as DNA, mixtures, populations of molecules, etc., that are very common in molecular biology. We present extensions that need to be made to an ontology to cover these issues: the representation of transformations that change the structure and/or category of their participants, and the component relations and spatial structures of complex objects. We demonstrate examples of how the proposed representations can be used to improve the quality and completeness of answers to user queries; discuss techniques for evaluating ontologies and show a prototype of an Information Retrieval System that we developed.
    Content
    Submitted in partial fulfillment of the requirements for the Degree of Doctor of Philosophy in Computer Science in the College of Computer Science at Northeastern University, Boston, MA. Vgl.: http://www.stanford.edu/~natalya/papers/Thesis.pdf.
  11. Thornton, K: Powerful structure : inspecting infrastructures of information organization in Wikimedia Foundation projects (2016) 0.04 
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    Abstract
    This dissertation investigates the social and technological factors of collaboratively organizing information in commons-based peer production systems. To do so, it analyzes the diverse strategies that members of Wikimedia Foundation (WMF) project communities use to organize information. Key findings from this dissertation show that conceptual structures of information organization are encoded into the infrastructure of WMF projects. The fact that WMF projects are commons-based peer production systems means that we can inspect the code that enables these systems, but a specific type of technical literacy is required to do so. I use three methods in this dissertation. I conduct a qualitative content analysis of the discussions surrounding the design, implementation and evaluation of the category system; a quantitative analysis using descriptive statistics of patterns of editing among editors who contributed to the code of templates for information boxes; and a close reading of the infrastructure used to create the category system, the infobox templates, and the knowledge base of structured data.
    Footnote
    A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Washington.
  12. Smith, D.A.: Exploratory and faceted browsing over heterogeneous and cross-domain data sources. (2011) 0.04 
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    Abstract
    Exploration of heterogeneous data sources increases the value of information by allowing users to answer questions through exploration across multiple sources; Users can use information that has been posted across the Web to answer questions and learn about new domains. We have conducted research that lowers the interrogation time of faceted data, by combining related information from different sources. The work contributes methodologies in combining heterogenous sources, and how to deliver that data to a user interface scalably, with enough performance to support rapid interrogation of the knowledge by the user. The work also contributes how to combine linked data sources so that users can create faceted browsers that target the information facets of their needs. The work is grounded and proven in a number of experiments and test cases that study the contributions in domain research work.
    Footnote
    A thesis submitted in partial fulfillment for the degree of Doctor of Philosophy. June 2011.
    Imprint
    Southampton : University, Faculty of Physical and Applied Sciences, Electronics and Computer Science
  13. Styltsvig, H.B.: Ontology-based information retrieval (2006) 0.03 
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    Abstract
    In this thesis, we will present methods for introducing ontologies in information retrieval. The main hypothesis is that the inclusion of conceptual knowledge such as ontologies in the information retrieval process can contribute to the solution of major problems currently found in information retrieval. This utilization of ontologies has a number of challenges. Our focus is on the use of similarity measures derived from the knowledge about relations between concepts in ontologies, the recognition of semantic information in texts and the mapping of this knowledge into the ontologies in use, as well as how to fuse together the ideas of ontological similarity and ontological indexing into a realistic information retrieval scenario. To achieve the recognition of semantic knowledge in a text, shallow natural language processing is used during indexing that reveals knowledge to the level of noun phrases. Furthermore, we briefly cover the identification of semantic relations inside and between noun phrases, as well as discuss which kind of problems are caused by an increase in compoundness with respect to the structure of concepts in the evaluation of queries. Measuring similarity between concepts based on distances in the structure of the ontology is discussed. In addition, a shared nodes measure is introduced and, based on a set of intuitive similarity properties, compared to a number of different measures. In this comparison the shared nodes measure appears to be superior, though more computationally complex. Some of the major problems of shared nodes which relate to the way relations differ with respect to the degree they bring the concepts they connect closer are discussed. A generalized measure called weighted shared nodes is introduced to deal with these problems. Finally, the utilization of concept similarity in query evaluation is discussed. A semantic expansion approach that incorporates concept similarity is introduced and a generalized fuzzy set retrieval model that applies expansion during query evaluation is presented. While not commonly used in present information retrieval systems, it appears that the fuzzy set model comprises the flexibility needed when generalizing to an ontology-based retrieval model and, with the introduction of a hierarchical fuzzy aggregation principle, compound concepts can be handled in a straightforward and natural manner.
    Content
    A dissertation Presented to the Faculties of Roskilde University in Partial Fulfillment of the Requirement for the Degree of Doctor of Philosophy. Vgl. unter: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.117.987 oder http://coitweb.uncc.edu/~ras/RS/Onto-Retrieval.pdf.
  14. Strong, R.W.: Undergraduates' information differentiation behaviors in a research process : a grounded theory approach (2005) 0.03 
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    Abstract
    This research explores, using a Grounded Theory approach, the question of how a particular group of undergraduate university students differentiates the values of retrieved information in a contemporary research process. Specifically it attempts to isolate and label those specific techniques, processes, formulae-both objective and subjective-that the students use to identify, prioritize, and successfully incorporate the most useful and valuable information into their research project. The research reviews the relevant literature covering the areas of: epistemology, knowledge acquisition, and cognitive learning theory; early relevance research; the movement from relevance models to information seeking in context; and the proximate recent research. A research methodology is articulated using a Grounded Theory approach, and the research process and research participants are fully explained and described. The findings of the research are set forth using three Thematic Sets- Traditional Relevance Measures; Structural Frames; and Metaphors: General and Ecological-using the actual discourse of the study participants, and a theoretical construct is advanced. Based on that construct, it can be theorized that identification and analysis of the metaphorical language that the particular students in this study used, both by way of general and ecological metaphors-their stories-about how they found, handled, and evaluated information, can be a very useful tool in understanding how the students identified, prioritized, and successfully incorporated the most useful and relevant information into their research projects. It also is argued that this type of metaphorical analysis could be useful in providing a bridging mechanism for a broader understanding of the relationships between traditional user relevance studies and the concepts of frame theory and sense-making. Finally, a corollary to Whitmire's original epistemological hypothesis is posited: Students who were more adept at using metaphors-either general or ecological-appeared more comfortable with handling contradictory information sources, and better able to articulate their valuing decisions. The research concludes with a discussion of the implications for both future research in the Library and Information Science field, and for the practice of both Library professionals and classroom instructors involved in assisting students involved in information valuing decision-making in a research process.
    Content
    Dissertation Presented to the Faculty of the Graduate School of The University of Texas at Austin in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy. Vgl. unter: http://dspace.lib.utexas.edu/bitstream/2152/701/1/strongr80063.pdf.
    Imprint
    Austin, TX : University of Texas at Austin
  15. Sebastian, Y.: Literature-based discovery by learning heterogeneous bibliographic information networks (2017) 0.03 
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    Abstract
    Literature-based discovery (LBD) research aims at finding effective computational methods for predicting previously unknown connections between clusters of research papers from disparate research areas. Existing methods encompass two general approaches. The first approach searches for these unknown connections by examining the textual contents of research papers. In addition to the existing textual features, the second approach incorporates structural features of scientific literatures, such as citation structures. These approaches, however, have not considered research papers' latent bibliographic metadata structures as important features that can be used for predicting previously unknown relationships between them. This thesis investigates a new graph-based LBD method that exploits the latent bibliographic metadata connections between pairs of research papers. The heterogeneous bibliographic information network is proposed as an efficient graph-based data structure for modeling the complex relationships between these metadata. In contrast to previous approaches, this method seamlessly combines textual and citation information in the form of pathbased metadata features for predicting future co-citation links between research papers from disparate research fields. The results reported in this thesis provide evidence that the method is effective for reconstructing the historical literature-based discovery hypotheses. This thesis also investigates the effects of semantic modeling and topic modeling on the performance of the proposed method. For semantic modeling, a general-purpose word sense disambiguation technique is proposed to reduce the lexical ambiguity in the title and abstract of research papers. The experimental results suggest that the reduced lexical ambiguity did not necessarily lead to a better performance of the method. This thesis discusses some of the possible contributing factors to these results. Finally, topic modeling is used for learning the latent topical relations between research papers. The learned topic model is incorporated into the heterogeneous bibliographic information network graph and allows new predictive features to be learned. The results in this thesis suggest that topic modeling improves the performance of the proposed method by increasing the overall accuracy for predicting the future co-citation links between disparate research papers.
    Footnote
    A thesis submitted in ful llment of the requirements for the degree of Doctor of Philosophy Monash University, Faculty of Information Technology.
  16. Gordon, T.J.; Helmer-Hirschberg, O.: Report on a long-range forecasting study (1964) 0.02 
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    Abstract
    Description of an experimental trend-predicting exercise covering a time period as far as 50 years into the future. The Delphi technique is used in soliciting the opinions of experts in six areas: scientific breakthroughs, population growth, automation, space progress, probability and prevention of war, and future weapon systems. Possible objections to the approach are also discussed.
    Date
    22. 6.2018 13:24:08
    22. 6.2018 13:54:52
  17. Makewita, S.M.: Investigating the generic information-seeking function of organisational decision-makers : perspectives on improving organisational information systems (2002) 0.01 
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    Abstract
    The past decade has seen the emergence of a new paradigm in the corporate world where organisations emphasised connectivity as a means of exposing decision-makers to wider resources of information within and outside the organisation. Many organisations followed the initiatives of enhancing infrastructures, manipulating cultural shifts and emphasising managerial commitment for creating pools and networks of knowledge. However, the concept of connectivity is not merely presenting people with the data, but more importantly, to create environments where people can seek information efficiently. This paradigm has therefore caused a shift in the function of information systems in organisations. They have to be now assessed in relation to how they underpin people's information-seeking activities within the context of their organisational environment. This research project used interpretative research methods to investigate the nature of people's information-seeking activities at two culturally contrasting organisations. Outcomes of this research project provide insights into phenomena associated with people's information-seeking function, and show how they depend on the organisational context that is defined partly by information systems. It suggests that information-seeking is not just searching for data. The inefficiencies inherent in both people and their environments can bring opaqueness into people's data, which they need to avoid or eliminate as part of seeking information. This seems to have made information-seeking a two-tier process consisting of a primary process of searching and interpreting data and auxiliary process of avoiding and eliminating opaqueness in data. Based on this view, this research suggests that organisational information systems operate naturally as implicit dual-mechanisms to underpin the above two-tier process, and that improvements to information systems should concern maintaining the balance in these dual-mechanisms.
    Date
    22. 7.2022 12:16:58
  18. Francu, V.: Multilingual access to information using an intermediate language (2003) 0.01 
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    Abstract
    While being theoretically so widely available, information can be restricted from a more general use by linguistic barriers. The linguistic aspects of the information languages and particularly the chances of an enhanced access to information by means of multilingual access facilities will make the substance of this thesis. The main problem of this research is thus to demonstrate that information retrieval can be improved by using multilingual thesaurus terms based on an intermediate or switching language to search with. Universal classification systems in general can play the role of switching languages for reasons dealt with in the forthcoming pages. The Universal Decimal Classification (UDC) in particular is the classification system used as example of a switching language for our objectives. The question may arise: why a universal classification system and not another thesaurus? Because the UDC like most of the classification systems uses symbols. Therefore, it is language independent and the problems of compatibility between such a thesaurus and different other thesauri in different languages are avoided. Another question may still arise? Why not then, assign running numbers to the descriptors in a thesaurus and make a switching language out of the resulting enumerative system? Because of some other characteristics of the UDC: hierarchical structure and terminological richness, consistency and control. One big problem to find an answer to is: can a thesaurus be made having as a basis a classification system in any and all its parts? To what extent this question can be given an affirmative answer? This depends much on the attributes of the universal classification system which can be favourably used to this purpose. Examples of different situations will be given and discussed upon beginning with those classes of UDC which are best fitted for building a thesaurus structure out of them (classes which are both hierarchical and faceted)...
    Content
    Inhalt: INFORMATION LANGUAGES: A LINGUISTIC APPROACH MULTILINGUAL ASPECTS IN INFORMATION STORAGE AND RETRIEVAL COMPATIBILITY AND CONVERTIBILITY OF INFORMATION LANGUAGES CURRENT TRENDS IN MULTILINGUAL ACCESS BUILDING UDC-BASED MULTILINGUAL THESAURI ONLINE APPLICATIONS OF THE UDC-BASED MULTILINGUAL THESAURI THE IMPACT OF SPECIFICITY ON THE RETRIEVAL POWER OF A UDC-BASED MULTILINGUAL THESAURUS FINAL REMARKS AND GENERAL CONCLUSIONS Proefschrift voorgelegd tot het behalen van de graad van doctor in de Taal- en Letterkunde aan de Universiteit Antwerpen. - Vgl.: http://dlist.sir.arizona.edu/1862/.
  19. Schwarz, K.: Domain model enhanced search : a comparison of taxonomy, thesaurus and ontology (2005) 0.01 
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    Abstract
    The results of this thesis are intended to support the information architect in designing a solution for improved search in a corporate environment. Specifically we have examined the type of search problems that require a domain model to enhance the search process. There are several approaches to modeling a domain. We have considered 3 different types of domain modeling schemes; taxonomy, thesaurus and ontology. The intention is to support the information architect in making an informed choice between one or more of these schemes. In our opinion the main criteria for this choice are the modeling characteristics of a scheme and the suitability for application in the search process. The second chapter is a discussion of modeling characteristics of each scheme, followed by a comparison between them. This should give an information architect an idea of which aspects of a domain can be modeled with each scheme. What is missing here is an indication of the effort required to model a domain with each scheme. There are too many factors that influence the amount of required effort, ranging from measurable factors like domain size and resource characteristics to cultural matters such as the willingness to share knowledge and the existence of a project champion in the team to keep the project running. The third chapter shows what role domain models can play in each part of the search process. This gives an idea of the problems that domain models can solve. We have split the search process into individual parts to show that domain models can be applied very differently in the process. The fourth chapter makes recommendations about the suitability of each individualdomain modeling scheme for improving search. Each scheme has particular characteristics that make it especially suitable for a domain or a search problem. In the appendix each case study is described in detail. These descriptions are intended to serve as a benchmark. The current problem of the enterprise can be compared to those described to see which case study is most similar, which solution was chosen, which problems arose and how they were dealt with. An important issue that we have not touched upon in this thesis is that of maintenance. The real problems of a domain model are revealed when it is applied in a search system and its deficits and wrong assumptions become clear. Adaptation and maintenance are always required. Unfortunately we have not been able to glean sufficient information about maintenance issues from our case studies to draw any meaningful conclusions.
    Content
    Master of Content and Knowledge Engineering
  20. Garfield, E.: ¬An algorithm for translating chemical names to molecular formulas (1961) 0.01 
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    Abstract
    This dissertation discusses, explains, and demonstrates a new algorithm for translating chemica l nomenclature into molecular formulas. In order to place the study in its proper context and perspective the historical development of nomenclature is first discussed, aa well as other related aspects of the chemical information problem. The relationship of nomenclature to modern linguistic studies is then introduced. Tire relevance of structural linguistic procedures to the study of chemical nomenclature is shown. The methods of the linguist are illustrated by examples from chemical discourse. The algorithm is then explained, first for the human translator and then for use by a computer. Flow diagrams for the computer syntactic analysis, dictionary Iook-up routine, and furmula calculation routine are included. The sampling procedure for testing the algorithm is explained and finalIy, conclusions are drawn with respect to the general validity of the method and the dirsction that might be taken for future research. A summary of modern chemical nomenclature practice is appened primarily for use by the reader who is not familiar with chemical nomenclature.
    Content
    Doctoral dissertation, University of Pennsylvania, 1961. Vgl..: http://www.garfield.library.upenn.edu/essays/v7p441y1984.pdf. Auch in: Essays of an information scientist. Vol. 7. Philadelphia, PA: ISI Press, 1985. S.441-513.
    Imprint
    University of Pennsylvania : Philadelphia, PA

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