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Web Application for Intuitive Composition of Text Filters
Sadílek, Jakub ; Kolář, Martin (referee) ; Herout, Adam (advisor)
The aim of this thesis is to provide intuitive and easy to use tool for advanced text filtration with the option of easy prototyping and tuning, without the necessity to know programming techniques. The basic principle is the choice of text tools and their inserting into the sequence, so called pipeline, which is typical for shell, from which the application draws inspiration. Tools can be also additionally edited or swapped. The application is aimed primarily at users unfamiliar with this principle or at programmers, for whom it is time-efficient to have their text modified this way and afterwards generate equivalent shell expression. Another way of tuning is realized using so called breakpoints, through which it is easy to quickly focus on chosen lines of the text. This way, the application offers functionality in two separated modes, between which the users can switch anytime according to their needs.
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Moving from Find & Get and Towards Use & Understanding
Morgan Lease, Eric
Considering the ubiquitous nature of networked computers, the traditional role of libraries is not as critical as it used to be. In other words, the time-honored library activities of collection, organization, preservation, and dissemination of books & journals is quickly being supplanted by the ever-present Google search. Thus, the problem to solve is less about finding & getting information but rather about using & understanding the information found. We continue to drink from the proverbial firehose. This does not foretell the demise of libraries nor librarians. Instead, it represents an opportunity to provide enhanced and value-added services above and beyond our collections. These services can be articulated as action statements such as but not limited to: analyze; annotate; cite; cluster & classify; compare & contrast; confirm; count & tabulate words, phrases, and ideas; delete; discuss, evaluate; find opposite; find similar; graph & visualize; learn from; plot on a map; plot on a timeline; purchase, rate; read at a distance; read closely; read at scale; review; save; share; summarize; tag; trace idea; transform; etc. This presentation elaborates upon these ideas with an emphasis on the possibilities of natural language processing & text mining in libraries.
Video:  MP4
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Recommender System for Web Articles
Kočí, Jan ; Kesiraju, Santosh (referee) ; Fajčík, Martin (advisor)
Tématem této bakalářské práce jsou doporučovací systémy pro webové články. Tato práce nejdříve uvádí nejpopulárnější metody z této oblasti a vysvětluje jejich principy, následně navrhuje požití vlastní architektury, založené na neuronových sítích, která aplikuje metodu Skip-gram negative sampling na problematiku doporučování. V další části pak implementuje tuto architekturu společně s několika dalšími modely, požívající algoritmus SVD, collaborative filtering s algoritmem ALS a také metodu Doc2Vec k vytvoření vektorové reprezentace z obsahu získaných článků. Na závěr vytváří tři evaluační metriky, konkrétně metriky RANK, Recall at k a Precision at k, a vyhodnocuje kvalitu implementovaných modelů srovnáním výsledků s nejmodernějšími modely. Kromě toho také diskutuje o roli a smyslu doporučovacích systémů ve společnosti a uvádí motivaci pro jejich používání.
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Semantic Enrichment Component
Doležal, Jan ; Otrusina, Lubomír (referee) ; Dytrych, Jaroslav (advisor)
This master's thesis describes Semantic Enrichment Component (SEC), that searches entities (e.g., persons or places) in the input text document and returns information about them. The goals of this component are to create a single interface for named entity recognition tools, to enable parallel document processing, to save memory while using the knowledge base, and to speed up access to its content. To achieve these goals, the output of the named entity recognition tools in the text was specified, the tool for storing the preprocessed knowledge base into the shared memory was implemented, and the client-server scheme was used to create the component.
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Shlukování textových dokumentů a jejich částí
Zápotocký, Radoslav ; Kopecký, Michal (advisor) ; Skopal, Tomáš (referee)
This thesis analyses use of vector-space model and data clustering approaches on parts of single document - on chapters, paragraphs and sentences - to allow simple navigation between similar parts. A simulation application (SimDIS), written in C# programming language is also part of this thesis. The application implements the described model and provides tools for visualization of vectors and clusters.
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Shlukování textových dokumentů a jejich částí
Zápotocký, Radoslav ; Kopecký, Michal (advisor) ; Skopal, Tomáš (referee)
This thesis analyses use of vector-space model and data clustering approaches on parts of single document - on chapters, paragraphs and sentences. A simulation application (SimDIS), written in C# programming language is also part of this thesis. The application implements the adjusted model and provides tools for visualization of vectors and clusters.
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Recognition of emotions in text using artificial intelligence
Vylíčil, Radek ; Karásek, Jan (referee) ; Mašek, Jan (advisor)
This thesis deals with the recognition of emotions from text using machine learning. The text describes methods how to train and test an recognition models. The main contribution of this thesis consists in creation decision tree in Java programming language. Created algorithm was integrated as plugin into the RapidMiner tool. The thesis contains some created examples for executing in RapidMiner. The functionality of decision tree was demonstrated on created database.
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Options of automated categorization of contracts
Bereš, Miroslav ; Jelínek, Ivan (advisor) ; Oškera, Radek (referee)
My bachelor thesis is focused on automatic categorization. The main goal is to examine actual approaches in automatic categorization, propose methodology for an experiment and perform the experiment. The experiment is done in order to measure success rate of automatic categorization with use of machine learning. It is performed on contracts obtained from public administration's web pages. The bachelor is divided into two parts, theoretical part and the experiment. First one focuses on analyzing theory which explains the subject matter, there are also described current approaches in automatic categorization. Second part describes methodology proposal of the experiment and performing of the experiment. During the process of the experiment, there are created models that are applied on control group. The experiment's outputs are categorized documents. These documents are used to monitor the success rate of automatic categorization. In order to measure the success rate, there is software called Apache OpenNLP used in this experiment. The theoretical part and proposal of the methodology are written based on studying foreign professional literature, mostly obtained from electronic and information sources.
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