493 resultados para Automatized Indexing
Resumo:
Terrain can be approximated by a triangular mesh consisting millions of 3D points. Multiresolution triangular mesh (MTM) structures are designed to support applications that use terrain data at variable levels of detail (LOD). Typically, an MTM adopts a tree structure where a parent node represents a lower-resolution approximation of its descendants. Given a region of interest (ROI) and a LOD, the process of retrieving the required terrain data from the database is to traverse the MTM tree from the root to reach all the nodes satisfying the ROI and LOD conditions. This process, while being commonly used for multiresolution terrain visualization, is inefficient as either a large number of sequential I/O operations or fetching a large amount of extraneous data is incurred. Various spatial indexes have been proposed in the past to address this problem, however level-by-level tree traversal remains a common practice in order to obtain topological information among the retrieved terrain data. A new MTM data structure called direct mesh is proposed. We demonstrate that with direct mesh the amount of data retrieval can be substantially reduced. Comparing with existing MTM indexing methods, a significant performance improvement has been observed for real-life terrain data.
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Few works address methodological issues of how to conduct strategy-as-practice research and even fewer focus on how to analyse the subsequent data in ways that illuminate strategy as an everyday, social practice. We address this gap by proposing a quantitative method for analysing observational data, which can complement more traditional qualitative methodologies. We propose that rigorous but context-sensitive coding of transcripts can render everyday practice analysable statistically. Such statistical analysis provides a means for analytically representing patterns and shifts within the mundane, repetitive elements through which practice is accomplished. We call this approach the Event Database (EDB) and it consists of five basic coding categories that help us capture the stream of practice. Indexing codes help to index or categorise the data, in order to give context and offer some basic information about the event under discussion. Indexing codes are descriptive codes, which allow us to catalogue and classify events according to their assigned characteristics. Content codes are to do with the qualitative nature of the event; this is the essence of the event. It is a description that helps to inform judgements about the phenomenon. Nature codes help us distinguish between discursive and tangible events. We include this code to acknowledge that some events differ qualitatively from other events. Type events are codes abstracted from the data in order to help us classify events based on their description or nature. This involves significantly more judgement than the index codes but consequently is also more meaningful. Dynamics codes help us capture some of the movement or fluidity of events. This category has been included to let us capture the flow of activity over time.
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This paper summarizes the scientific work presented at the 32nd European Conference on Information Retrieval. It demonstrates that information retrieval (IR) as a research area continues to thrive with progress being made in three complementary sub-fields, namely IR theory and formal methods together with indexing and query representation issues, furthermore Web IR as a primary application area and finally research into evaluation methods and metrics. It is the combination of these areas that gives IR its solid scientific foundations. The paper also illustrates that significant progress has been made in other areas of IR. The keynote speakers addressed three such subject fields, social search engines using personalization and recommendation technologies, the renewed interest in applying natural language processing to IR, and multimedia IR as another fast-growing area.
Resumo:
Few works address methodological issues of how to conduct strategy-as-practice research and even fewer focus on how to analyse the subsequent data in ways that illuminate strategy as an everyday, social practice. We address this gap by proposing a quantitative method for analysing observational data, which can complement more traditional qualitative methodologies. We propose that rigorous but context-sensitive coding of transcripts can render everyday practice analysable statistically. Such statistical analysis provides a means for analytically representing patterns and shifts within the mundane, repetitive elements through which practice is accomplished. We call this approach the Event Database (EDB) and it consists of five basic coding categories that help us capture the stream of practice. Indexing codes help to index or categorise the data, in order to give context and offer some basic information about the event under discussion. Indexing codes are descriptive codes, which allow us to catalogue and classify events according to their assigned characteristics. Content codes are to do with the qualitative nature of the event; this is the essence of the event. It is a description that helps to inform judgements about the phenomenon. Nature codes help us distinguish between discursive and tangible events. We include this code to acknowledge that some events differ qualitatively from other events. Type events are codes abstracted from the data in order to help us classify events based on their description or nature. This involves significantly more judgement than the index codes but consequently is also more meaningful. Dynamics codes help us capture some of the movement or fluidity of events. This category has been included to let us capture the flow of activity over time.
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The essential first step for a beginning reader is to learn to match printed forms to phonological representations. For a new word, this is an effortful process where each grapheme must be translated individually (serial decoding). The role of phonological awareness in developing a decoding strategy is well known. We examined whether beginner readers recruit different skills depending on the nature of the words being read (familiar words vs. nonwords). Print knowledge, phoneme and rhyme awareness, rapid automatized naming (RAN), phonological short term memory (STM), nonverbal reasoning, vocabulary, auditory skills and visual attention were measured in 392 pre-readers aged 4 to 5 years. Word and nonword reading were measured 9 months later. We used structural equation modeling to examine the skills-reading relationship and modeled correlations between our two reading outcomes and among all pre-reading skills. We found that a broad range of skills were associated with reading outcomes: early print knowledge, phonological STM, phoneme awareness and RAN. Whereas all these skills were directly predictive of nonword reading, early print knowledge was the only direct predictor of word reading. Our findings suggest that beginner readers draw most heavily on their existing print knowledge to read familiar words.
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Readers may have noted that a short but very important announcement was made in the last issue of CLAE, at the top of the contents page. CLAE has been accepted by Thomson Reuters for abstracting and indexing in its SciSearch, Journal Citation Reports, and Current Contents services. This will ensure a greater visibility to the international research community. In addition, in June 2012 CLAE will receive its very first official Impact Factor – a measure of journal influence of importance to authors and readers alike. The impact factor value has not yet been decided but internal estimates by Elsevier estimate it will be around 1, and it will be applied to all CLAE issue back to January 2009 (volume 32). I would guess readers at this stage would have one of two responses – either ‘that's good news’ or perhaps ‘what's an impact factor?’ If you are in the latter camp then allow me to try and explain. Basically the impact factor or citation index of a journal is based on how many times in the previous year papers published in that journal in the previous two years were cited by authors publishing in other journals. So the 2012 impact factor for CLAE is calculated on how many times in 2011 papers that were published in CLAE in 2010 and 2009 were cited in other journals in 2011, divided by the number of papers published in CLAE 2010 and 2009. Essentially authors will try and get their work published in journals with a higher impact factor as it is thought that the paper will be cited more by other authors or the paper will have higher visibility in the arena. For universities having its published output in higher journals is one of the markers used to judge esteem. For individual authors publishing in journals with a higher impact factor or the number of times one of their papers is published is something that they are likely to add to their CVs or demonstrate the importance of their work. Journals with higher impact factors tend to be more review journals or journals with a wider spectrum so for a relatively small journal with a specialised field like CLAE it is great to be listed with a citation index. The awarding of a citation index crowns many changes that CLAE has undergone since the current Editor took the reins in 2005. CLAE has increased from four issues (in 2004) to six issues per year with at least one review article per issue and one article with continuing education per issue. The rejection rate has gone up significantly meaning that only best papers are published (currently it stands at 37%). CLAE has been Medline/Pubmed indexed for a few years now which is also a very important factor in improving visibility of the journal. The submission and reviewing process for CLAE in now entirely online and finally the editorial board has changed from being merely a list of keynote people to being an active group of keynote people who are enthusiastically involved with the journal. From the editorial board one person is appointed as a Reviews Editor plus we have two additional editors who work as Regional Editors. As ever, on behalf of CLAE I would like to thank the BCLA Council for their continued support (especially Vivien Freeman) and Elsevier for their continuing guidance (in particular Andrew Miller and Rosie Davey) and the excellent Editorial Board (Christopher Snyder, Pauline Cho, Eric Papas, Jan Bergmanson, Roger Buckley, Patrick Caroline, Dwight Cavanagh, Robin Chalmers, Michael Doughty, Nathan Efron, Michel Guillon, Nizar Hirji, Meng Lin, Florence Malet, Philip Morgan, Deborah Sweeney, Brian Tighe, Eef van Der Worp, Barry Weissman, Mark Willcox, James Wolffsohn and Craig Woods). And finally, a big thanks to the authors and reviewers who work tirelessly putting manuscripts together for publication in CLAE. Copyright © 2012 Published by Elsevier Ltd.
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Background Qualitative research makes an important contribution to our understanding of health and healthcare. However, qualitative evidence can be difficult to search for and identify, and the effectiveness of different types of search strategies is unknown. Methods Three search strategies for qualitative research in the example area of support for breast-feeding were evaluated using six electronic bibliographic databases. The strategies were based on using thesaurus terms, free-text terms and broad-based terms. These strategies were combined with recognised search terms for support for breast-feeding previously used in a Cochrane review. For each strategy, we evaluated the recall (potentially relevant records found) and precision (actually relevant records found). Results A total yield of 7420 potentially relevant records was retrieved by the three strategies combined. Of these, 262 were judged relevant. Using one strategy alone would miss relevant records. The broad-based strategy had the highest recall and the thesaurus strategy the highest precision. Precision was generally poor: 96% of records initially identified as potentially relevant were deemed irrelevant. Searching for qualitative research involves trade-offs between recall and precision. Conclusions These findings confirm that strategies that attempt to maximise the number of potentially relevant records found are likely to result in a large number of false positives. The findings also suggest that a range of search terms is required to optimise searching for qualitative evidence. This underlines the problems of current methods for indexing qualitative research in bibliographic databases and indicates where improvements need to be made.
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In this paper we study some of the characteristics of the art painting image color semantics. We analyze the color features of differ- ent artists and art movements. The analysis includes exploration of hue, saturation and luminance. We also use quartile’s analysis to obtain the dis- tribution of the dispersion of defined groups of paintings and measure the degree of purity for these groups. A special software system “Art Paint- ing Image Color Semantics” (APICSS) for image analysis and retrieval was created. The obtained result can be used for automatic classification of art paintings in image retrieval systems, where the indexing is based on color characteristics.
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Search engines sometimes apply the search on the full text of documents or web-pages; but sometimes they can apply the search on selected parts of the documents only, e.g. their titles. Full-text search may consume a lot of computing resources and time. It may be possible to save resources by applying the search on the titles of documents only, assuming that a title of a document provides a concise representation of its content. We tested this assumption using Google search engine. We ran search queries that have been defined by users, distinguishing between two types of queries/users: queries of users who are familiar with the area of the search, and queries of users who are not familiar with the area of the search. We found that searches which use titles provide similar and sometimes even (slightly) better results compared to searches which use the full-text. These results hold for both types of queries/users. Moreover, we found an advantage in title-search when searching in unfamiliar areas because the general terms used in queries in unfamiliar areas match better with general terms which tend to be used in document titles.
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This paper describes the followed methodology to automatically generate titles for a corpus of questions that belong to sociological opinion polls. Titles for questions have a twofold function: (1) they are the input of user searches and (2) they inform about the whole contents of the question and possible answer options. Thus, generation of titles can be considered as a case of automatic summarization. However, the fact that summarization had to be performed over very short texts together with the aforementioned quality conditions imposed on new generated titles led the authors to follow knowledge-rich and domain-dependent strategies for summarization, disregarding the more frequent extractive techniques for summarization.
Resumo:
В статье рассмотрена проблема семантической разницы между содержимым мультимедиа и его текстовым описанием, определяемым вручную. Предложен комбинированный подход к представлению семантики мультимедиа, основанный на объединении близких по содержанию и текстовому описанию мультимедиа в классы, содержащие обобщённые описания объектов, связей между ними и ключевых слов текстовых метаданных из некоторого тезауруса. Для формирования этих классов используются операции иерархической кластеризации и машинного обучения. Данный подход позволяет расширить область поиска и навигации мультимедиа благодаря привлечению медиа-данных, имеющих схожее содержание и текстовое описание.
Resumo:
As the volume of image data and the need of using it in various applications is growing significantly in the last days it brings a necessity of retrieval efficiency and effectiveness. Unfortunately, existing indexing methods are not applicable to a wide range of problem-oriented fields due to their operating time limitations and strong dependency on the traditional descriptors extracted from the image. To meet higher requirements, a novel distance-based indexing method for region-based image retrieval has been proposed and investigated. The method creates premises for considering embedded partitions of images to carry out the search with different refinement or roughening level and so to seek the image meaningful content.
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AMS Subj. Classification: H.3.7 Digital Libraries, K.6.5 Security and Protection
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In the recent years the East-Christian iconographical art works have been digitized providing a large volume of data. The need for effective classification, indexing and retrieval of iconography repositories was the motivation of the design and development of a systemized ontological structure for description of iconographical art objects. This paper presents the ontology of the East-Christian iconographical art, developed to provide content annotation in the Virtual encyclopedia of Bulgarian iconography multimedia digital library. The ontology’s main classes, relations, facts, rules, and problems appearing during the design and development are described. The paper also presents an application of the ontology for learning analysis on an iconography domain implemented during the SINUS project “Semantic Technologies for Web Services and Technology Enhanced Learning”.
Resumo:
2000 Mathematics Subject Classification: 05E05, 14N10, 57R45.