Search (1066 results, page 1 of 54)

  • × language_ss:"e"
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  • × year_i:[2010 TO 2020}
  1. Zeng, Q.; Yu, M.; Yu, W.; Xiong, J.; Shi, Y.; Jiang, M.: Faceted hierarchy : a new graph type to organize scientific concepts and a construction method (2019) 0.24
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    Content
    Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
  2. Sauperl, S.A.: UDC as a standardisation method for providing titles of documents (2015) 0.01
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    Date
    10.11.2015 10:22:31
    Source
    Classification and authority control: expanding resource discovery: proceedings of the International UDC Seminar 2015, 29-30 October 2015, Lisbon, Portugal. Eds.: Slavic, A. u. M.I. Cordeiro
  3. Sartori, F.; Grazioli, L.: Metadata guiding kowledge engineering : a practical approach (2014) 0.01
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    Abstract
    This paper presents an approach to the analysis, design and development of Knowledge Based Systems based on the Knowledge Artifact concept. Knowledge Artifacts can be meant as means to acquire, represent and maintain knowledge involved in complex problem solving activities. A complex problem is typically made of a huge number of parts that are put together according to a first set of constraints (i.e. the procedural knowledge), dependable on the functional properties it must satisfy, and a second set of rules, dependable on what the expert thinks about the problem and how he/she would represent it. The paper illustrates a way to unify both types of knowledge into a Knowledge Artifact, exploiting Ontologies, Influence Nets and Task Structures formalisms and metadata paradigm.
    Source
    Metadata and semantics research: 8th Research Conference, MTSR 2014, Karlsruhe, Germany, November 27-29, 2014, Proceedings. Eds.: S. Closs et al
  4. Fluhr, C.: Crosslingual access to photo databases (2012) 0.01
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    Abstract
    This paper is about search of photos in photo databases of agencies which sell photos over the Internet. The problem is far from the behavior of photo databases managed by librarians and also far from the corpora generally used for research purposes. The descriptions use mainly single words and it is well known that it is not the best way to have a good search. This increases the problem of semantic ambiguity. This problem of semantic ambiguity is crucial for cross-language querying. On the other hand, users are not aware of documentation techniques and use generally very simple queries but want to get precise answers. This paper gives the experience gained in a 3 year use (2006-2008) of a cross-language access to several of the main international commercial photo databases. The languages used were French, English, and German.
    Date
    17. 4.2012 14:25:22
  5. Tanti, M.; Roux, P.; Carrieri, M.P.; Martinho, N.; Spire, B.: Exploiting the knowledge organization of health 2.0 to create strategic value in public health : an example of application to the problem of drug consumption rooms in France (2016) 0.01
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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
  6. Song, L.; Tso, G.; Fu, Y.: Click behavior and link prioritization : multiple demand theory application for web improvement (2019) 0.01
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    Abstract
    A common problem encountered in Web improvement is how to arrange the homepage links of a Website. This study analyses Web information search behavior, and applies the multiple demand theory to propose two models to help a visitor allocate time for multiple links. The process of searching is viewed as a formal choice problem in which the visitor attempts to choose from multiple Web links to maximize the total utility. The proposed models are calibrated to clickstream data collected from an educational institute over a seven-and-a-half month period. Based on the best fit model, a metric, utility loss, is constructed to measure the performance of each link and arrange them accordingly. Empirical results show that the proposed metric is highly efficient for prioritizing the links on a homepage and the methodology can also be used to study the feasibility of introducing a new function in a Website.
    Date
    6. 7.2019 19:37:29
  7. Giannella, C.: ¬An improved algorithm for unsupervised decomposition of a multi-author document (2016) 0.01
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    Abstract
    This article addresses the problem of unsupervised decomposition of a multi-author text document: identifying the sentences written by each author assuming the number of authors is unknown. An approach, BayesAD, is developed for solving this problem: apply a Bayesian segmentation algorithm, followed by a segment clustering algorithm. Results are presented from an empirical comparison between BayesAD and AK, a modified version of an approach published by Akiva and Koppel in 2013. BayesAD exhibited greater accuracy than AK in all experiments. However, BayesAD has a parameter that needs to be set and which had a nontrivial impact on accuracy. Developing an effective method for eliminating this need would be a fruitful direction for future work. When controlling for topic, the accuracy levels of BayesAD and AK were, in all but one case, worse than a baseline approach wherein one author was assumed to write all sentences in the input text document. Hence, room for improved solutions exists.
    Date
    22. 1.2016 14:08:11
  8. Mayo, D.; Bowers, K.: ¬The devil's shoehorn : a case study of EAD to ArchivesSpace migration at a large university (2017) 0.01
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    Abstract
    A band of archivists and IT professionals at Harvard took on a project to convert nearly two million descriptions of archival collection components from marked-up text into the ArchivesSpace archival metadata management system. Starting in the mid-1990s, Harvard was an alpha implementer of EAD, an SGML (later XML) text markup language for electronic inventories, indexes, and finding aids that archivists use to wend their way through the sometimes quirky filing systems that bureaucracies establish for their records or the utter chaos in which some individuals keep their personal archives. These pathfinder documents, designed to cope with messy reality, can themselves be difficult to classify. Portions of them are rigorously structured, while other parts are narrative. Early documents predate the establishment of the standard; many feature idiosyncratic encoding that had been through several machine conversions, while others were freshly encoded and fairly consistent. In this paper, we will cover the practical and technical challenges involved in preparing a large (900MiB) corpus of XML for ingest into an open-source archival information system (ArchivesSpace). This case study will give an overview of the project, discuss problem discovery and problem solving, and address the technical challenges, analysis, solutions, and decisions and provide information on the tools produced and lessons learned. The authors of this piece are Kate Bowers, Collections Services Archivist for Metadata, Systems, and Standards at the Harvard University Archive, and Dave Mayo, a Digital Library Software Engineer for Harvard's Library and Technology Services. Kate was heavily involved in both metadata analysis and later problem solving, while Dave was the sole full-time developer assigned to the migration project.
    Date
    31. 1.2017 13:29:56
  9. Liu, R.-L.: ¬A passage extractor for classification of disease aspect information (2013) 0.01
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    Abstract
    Retrieval of disease information is often based on several key aspects such as etiology, diagnosis, treatment, prevention, and symptoms of diseases. Automatic identification of disease aspect information is thus essential. In this article, I model the aspect identification problem as a text classification (TC) problem in which a disease aspect corresponds to a category. The disease aspect classification problem poses two challenges to classifiers: (a) a medical text often contains information about multiple aspects of a disease and hence produces noise for the classifiers and (b) text classifiers often cannot extract the textual parts (i.e., passages) about the categories of interest. I thus develop a technique, PETC (Passage Extractor for Text Classification), that extracts passages (from medical texts) for the underlying text classifiers to classify. Case studies on thousands of Chinese and English medical texts show that PETC enhances a support vector machine (SVM) classifier in classifying disease aspect information. PETC also performs better than three state-of-the-art classifier enhancement techniques, including two passage extraction techniques for text classifiers and a technique that employs term proximity information to enhance text classifiers. The contribution is of significance to evidence-based medicine, health education, and healthcare decision support. PETC can be used in those application domains in which a text to be classified may have several parts about different categories.
    Date
    28.10.2013 19:22:57
  10. Bourouni , A.; Noori, S.; Jafari, M.: Knowledge network creation methodology selection in project-based organizations : an empirical framework (2015) 0.01
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    Abstract
    Purpose - In today's knowledge-based economy, knowledge networks (KN) increasingly are becoming vital channels for pursuing strategic objectives in project-based organizations (PBO), in which the project is the basic organizational element in its operation. KN initiatives often are started with the selection of a creation methodology, which involves complex decisions for successful implementation. Thus, the purpose of this paper is to address this critical selection of methodology and proposes a holistic framework for selecting an appropriate methodology in this kind of flatter, speedier, and more flexible organizational form. Design/methodology/approach - In the first step, the study established a theoretical background addressing the problem of KN creation in PBO. The second step defined selection criteria based on extensive literature review. In the third step, a holistic framework was constructed based on different characteristics of existing methodologies categorized according to the selected criteria. Finally, the suggested framework was empirically tested in a project-based firm and the case study and the results are discussed. Findings - A holistic framework was determined by including different aspects of a KN such as network perspectives, tools and techniques, objectives, characteristics, capabilities, and approaches. The proposed framework consisted of ten existing KN methodologies that consider qualitative and quantitative dimensions with micro and macro approaches. Originality/value - The development of the theory of KN creation methodology is the main contribution of this research. The selection framework, which was theoretically and empirically grounded, has attempted to offer a more rational and less ambiguous solution to the KN methodology selection problem in PBO forms.
    Date
    20. 1.2015 18:30:22
    18. 9.2018 16:27:22
  11. Wlodarczyk, B.: Topic map as a method for the development of subject headings vocabulary : an introduction to the project of the National Library of Poland (2013) 0.01
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    Abstract
    Subject searches in the National Library of Poland catalog are still comprised of a significant number of all searches, but understanding and exploration of the National Library of Poland Subject Headings causes many problems, not only for the end-users, but also for many librarians. Another problem in the National Library of Poland is the insufficient use of relationships between the terms. The solution could be a properly designed Web application based on a topic map using appropriate visualization that supports indexing and information retrieval in the National Library of Poland. The article presents the main stages of a planned project.
    Date
    29. 5.2015 19:16:59
  12. Teal, W.: Alma enumerator : automating repetitive cataloging tasks with Python (2018) 0.01
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    Abstract
    In June 2016, the Warburg College library migrated to a new integrated library system, Alma. In the process, we lost the enumeration and chronology data for roughly 79,000 print serial item records. Re-entering all this data by hand seemed an unthinkable task. Fortunately, the information was recorded as free text in each item's description field. By using Python, Alma's API and much trial and error, the Wartburg College library was able to parse the serial item descriptions into enumeration and chronology data that was uploaded back into Alma. This paper discusses the design and feasibility considerations addressed in trying to solve this problem, the complications encountered during development, and the highlights and shortcomings of the collection of Python scripts that became Alma Enumerator.
    Date
    10.11.2018 16:29:37
  13. Mazzucchelli, A.; Sartori , F.: String similarity in CBR platforms : a preliminary study (2014) 0.01
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    Pages
    S.22-29
    Source
    Metadata and semantics research: 8th Research Conference, MTSR 2014, Karlsruhe, Germany, November 27-29, 2014, Proceedings. Eds.: S. Closs et al
  14. White, H.: Examining scientific vocabulary : mapping controlled vocabularies with free text keywords (2013) 0.01
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    Date
    29. 5.2015 19:09:22
  15. Andrade, T.C.; Dodebei, V.: Traces of digitized newspapers and bom-digital news sites : a trail to the memory on the internet (2016) 0.01
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    Date
    19. 1.2019 17:42:22
    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
  16. Ohly, P.: Dimensions of globality : a bibliometric analysis (2016) 0.01
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    Date
    20. 1.2019 11:22:31
    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
  17. Wang, S.; Koopman, R.: Embed first, then predict (2019) 0.01
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    Abstract
    Automatic subject prediction is a desirable feature for modern digital library systems, as manual indexing can no longer cope with the rapid growth of digital collections. It is also desirable to be able to identify a small set of entities (e.g., authors, citations, bibliographic records) which are most relevant to a query. This gets more difficult when the amount of data increases dramatically. Data sparsity and model scalability are the major challenges to solving this type of extreme multilabel classification problem automatically. In this paper, we propose to address this problem in two steps: we first embed different types of entities into the same semantic space, where similarity could be computed easily; second, we propose a novel non-parametric method to identify the most relevant entities in addition to direct semantic similarities. We show how effectively this approach predicts even very specialised subjects, which are associated with few documents in the training set and are more problematic for a classifier.
    Date
    29. 9.2019 12:18:42
  18. Bhatia, S.; Biyani, P.; Mitra, P.: Identifying the role of individual user messages in an online discussion and its use in thread retrieval (2016) 0.01
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    Abstract
    Online discussion forums have become a popular medium for users to discuss with and seek information from other users having similar interests. A typical discussion thread consists of a sequence of posts posted by multiple users. Each post in a thread serves a different purpose providing different types of information and, thus, may not be equally useful for all applications. Identifying the purpose and nature of each post in a discussion thread is thus an interesting research problem as it can help in improving information extraction and intelligent assistance techniques. We study the problem of classifying a given post as per its purpose in the discussion thread and employ features based on the post's content, structure of the thread, behavior of the participating users, and sentiment analysis of the post's content. We evaluate our approach on two forum data sets belonging to different genres and achieve strong classification performance. We also analyze the relative importance of different features used for the post classification task. Next, as a use case, we describe how the post class information can help in thread retrieval by incorporating this information in a state-of-the-art thread retrieval model.
    Date
    22. 1.2016 11:50:46
  19. Olivares-Rodríguez, C.; Guenaga, M.; Garaizar, P.: Using children's search patterns to predict the quality of their creative problem solving (2018) 0.01
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    Abstract
    Purpose The purpose of this paper is to propose a computational model that implicitly predict the children's creative quality of solutions by analyzing the query pattern on a problem-solving-based lesson. Design/methodology/approach A search task related to the competencies acquired in the classroom was applied to automatically measure children' creativity. A blind review process of the creative quality was developed of 255 primary school students' solutions. Findings While there are many creativity training programs that have proven effective, many of these programs require measuring creativity previously which involves time-consuming tasks conducted by experienced reviewers, i.e. far from primary school classroom dynamics. The authors have developed a model that predicts the creative quality of the given solution using the search queries pattern as input. This model has been used to predict the creative quality of 255 primary school students' solutions with 80 percent sensitivity. Research limitations/implications Although the research was conducted with just one search task, participants come from two different countries. Therefore, the authors hope that this model provides detection of non-creative solutions to enable prompt intervention and improve the creative quality of solutions. Originality/value This is the first implicit classification model of query pattern in order to predict the children' creative quality of solutions. This model is based on a conceptual relation between the concept association of creative thinking and query chain model of information search.
    Date
    20. 1.2015 18:30:22
  20. Qiu, X.Y.; Srinivasan, P.; Hu, Y.: Supervised learning models to predict firm performance with annual reports : an empirical study (2014) 0.01
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    Abstract
    Text mining and machine learning methodologies have been applied toward knowledge discovery in several domains, such as biomedicine and business. Interestingly, in the business domain, the text mining and machine learning community has minimally explored company annual reports with their mandatory disclosures. In this study, we explore the question "How can annual reports be used to predict change in company performance from one year to the next?" from a text mining perspective. Our article contributes a systematic study of the potential of company mandatory disclosures using a computational viewpoint in the following aspects: (a) We characterize our research problem along distinct dimensions to gain a reasonably comprehensive understanding of the capacity of supervised learning methods in predicting change in company performance using annual reports, and (b) our findings from unbiased systematic experiments provide further evidence about the economic incentives faced by analysts in their stock recommendations and speculations on analysts having access to more information in producing earnings forecast.
    Date
    29. 1.2014 16:46:40

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Themes