|
|
Query expansion for medical information retrieval
Bibyna, Feraena ; Pecina, Pavel (advisor) ; Holub, Martin (referee)
One of the challenges in medical information retrieval is the terminology gap between the documents (commonly written by medical professional, using medical jargons), and the queries (commonly composed by non professional, using layman terms). In this thesis, we investigate the effect of query expansion, using domain-specific knowledge resource, to deal with this challenge. We use the Unified Medical Language System (UMLS), a repository of biomedical vocabularies, and utilize two of its resources: the Metathesaurus and the Semantic Network. We use the query set and document set provided by CLEF eHealth organizer. The query sets, provided for the medical information retrieval shared task, represent two different use cases of medical information retrieval. We experiment with query expansion using synonymous terms and non-synonymous concepts, blind relevance feedback, field weighting, and linear interpolation of different systems. Powered by TCPDF (www.tcpdf.org)
|
|
|
Automatic suggestion of illustrative images
Odcházel, Ondřej ; Pecina, Pavel (advisor) ; Holub, Martin (referee)
The objective of this thesis is to implement a web application designed for recommendation of stock photos. The application gets the input from newspaper articles in Czech or English and, based on the text itself, suggests appropriate stock photos. The implemented application also searches images according to visual similarity. The thesis deals with theoretical aspects of keywords extraction and language of text detection. Further it analyzes possibilities of efficient search for similar vectors that are used in the search component for visually similar images. It also describes the possibilities in development of modern web frontend and backend. The quality of algorithm for recommending stock photos is tested on users. Powered by TCPDF (www.tcpdf.org)
|
|
|
Automatic construction of semantic networks
Kirschner, Martin ; Pecina, Pavel (advisor) ; Holub, Martin (referee)
Presented work explores the possibilities of automatic construction and expansion of semantic networks with use of machine learning methods. The main focus is put on the feature retrieving procedure for the data set. The work presents a method of semantic relation retrieval, based on distributional hypothesis and trained on the data from Czech WordNet. We also show the first results for Czech language in this area of research. Part of the thesis is also a set of software for processing and evaluating of input data and a overview and discussion about its results on real-world data. The resulting tools can process data of amount in orders of hundreds of millions of words. The research part of the thesis used Czech morphologically and syntactically annotated data, but the methods are not language dependent.
|
|
|
Combining text-based and vision-based semantics
Tran, Binh Giang ; Holub, Martin (advisor) ; Straková, Jana (referee)
Learning and representing semantics is one of the most important tasks that significantly contribute to some growing areas, as successful stories in the recent survey of Turney and Pantel (2010). In this thesis, we present an in- novative (and first) framework for creating a multimodal distributional semantic model from state of the art text-and image-based semantic models. We evaluate this multimodal semantic model on simulating similarity judgements, concept clustering and the newly introduced BLESS benchmark. We also propose an effective algorithm, namely Parameter Estimation, to integrate text- and image- based features in order to have a robust multimodal system. By experiments, we show that our technique is very promising. Across all experiments, our best multimodal model claims the first position. By relatively comparing with other text-based models, we are justified to affirm that our model can stay in the top line with other state of the art models. We explore various types of visual features including SIFT and other color SIFT channels in order to have prelim- inary insights about how computer-vision techniques should be applied in the natural language processing domain. Importantly, in this thesis, we show evi- dences that adding visual features (as the perceptual information coming from...
|
|
|
Automatic construction of semantic networks
Kirschner, Martin ; Pecina, Pavel (advisor) ; Holub, Martin (referee)
Presented work explores the possibilities of automatic construction and expansion of semantic networks with use of machine learning methods. The main focus is put on the feature retrieving procedure for the data set. The work presents a robust method of semantic relation retrieval, based on distributional hypothesis and trained on the data from Czech WordNet. We also show the first results for czech language in this area of research. Part of the thesis is also a set of software for processing and evaluating of input data and a overview and discussion about its results on real-world data. The resulting tools can process data of amount in orders of hundreds of millions of words. The research part of the thesis used Czech morphologicaly and syntacticaly annotated data, but the methods are not language dependent.
|
|
|
Classifier for semantic patterns of English verbs
Kríž, Vincent ; Holub, Martin (advisor) ; Bojar, Ondřej (referee)
The goal of the diploma thesis is to design, implement and evaluate classifiers for automatic classification of semantic patterns of English verbs according to a pattern lexicon that draws on the Corpus Pattern Analysis. We use a pilot collection of 30 sample English verbs as training and test data sets. We employ standard methods of machine learning. In our experiments we use decision trees, k-nearest neighbourghs (kNN), support vector machines (SVM) and Adaboost algorithms. Among other things we concentrate on feature design and selection. We experiment with both morpho-syntactic and semantic features. Our results show that the morpho-syntactic features are the most important for statistically-driven semantic disambiguation. Nevertheless, for some verbs the use of semantic features plays an important role.
|
|
|
Postmodernism in British and American comics : postmodernist overtones in the works of Alan Moore and Grant Morrison
Holub, Martin ; Ženíšek, Jakub (advisor) ; Chalupský, Petr (referee)
The aim of this thesis is the examination and analysis of postmodernist overtones in the medium of comics. It is concerned both with the postmodernist content in comics, and comics' possibilities and attributes as a postmodernist medium. The first part of the thesis elaborates on sequential art in general and the essential elements of postmodernism, such as deconstruction, metafiction, and intertextuality, within its context. The second part of the thesis is concerned with selected postmodernist works of prominent comicbook authors: Alan Moore and Grant Morrison. Key words Comics, comicbook, graphic novel, postmodernism, metafiction, intertextuality, continuum, narration, binary oppositions, deconstruction, superhero, author, creation, Watchmen, Animal Man
|
|
|
Typical Usage Patterns of English Verbs
Smejkalová, Lenka ; Holub, Martin (advisor) ; Lopatková, Markéta (referee)
Corpus Pattern Analysis (CPA) is a corpus-based method that explores typical usage patterns of verbs in a text corpus, and describes meaning of verbs by means of contextual preferences defined both syntactically and semantically [1]. CPA in conjuction with the British National Corpus (BNC) is currently used to create The Pattern Dictionary of English Verbs (PDEV) [1, 2]. The thesis describes the current status of the PDEV, presents a thorough analysis of available data on typical usage patterns and explores possible applications of the PDEV for automatic lexical analysis. In this thesis procedures usable in further PDEV development have been designed and implemented. The first of them automatically extracts arguments of verbs from an output of English syntactic analysis. The second one uses the extracted arguments to create lists of lexical units that realize semantic types. The last procedure uses these lists to automatically recognize typical usage patterns of verbs. The thesis also evaluates inter-annotator agreement, automatic extraction of verb arguments in/from English sentence, and effectiveness of the proposed procedures in the extraction of lexical units that realize semantic types and in automatic recognition of typical usage patterns.
|
|
|
Utilization of Modern Methods of Immobilization (casts), at Individuals with an Injury of Locomotive System, in The Czech Republic
Holub, Martin ; Levitová, Andrea (advisor) ; Hošková, Blanka (referee)
Title: Utilization of Modern Methods of Immobilization (casts), at Individuals with an Injury of Locomotive System, in The Czech Republic Objectives: The main objective of this thesis is to bring an actual information about proportion of using casts, in comparison with other methods of conservative immobilization, at individuals with an injury of locomotive system, in The Czech Republic. Moreover, the work aims to identify 3 most frequent reasons for using cast and 3 reasons for not using it. Methods: There is a sample of respondents, selected from professionals dealing with a treatment of locomotive system (n = 204). The sample consists of medical doctors working in hospitals (n = 67) as well as doctors working in out-patient ambulatory care segment (n = 137). With respect to doctors specialization, the sample consits of surgeons (n = 141) and orthopaedists (n = 63). Selection of the sample of respondents was randomized. Data were gathered by telephonic questioning (interview). Based on quantitative analysis of the data, both - relative usage of casts and three reasons supporting or limiting its utilization - were identified. The questionnaire was finalized, with respect to outcomes of an initial pilot study (n = 4). Respondents for the pilot study were chosen by quote selection. Results: Plaster...
|
|
| |
guest ::
