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Search results for: WIKIPEDIA
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Embedded Representations of Wikipedia Categories
PublicationIn this paper, we present an approach to building neural representations of the Wikipedia category graph. We test four different methods and examine the neural embeddings in terms of preservation of graphs edges, neighborhood coverage in representation space, and their influence on the results of a task predicting parent of two categories. The main contribution of this paper is application of neural representations for improving the...
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Wikipedia Articles Representation with Matrix'u
PublicationIn the article we evaluate different text representation methods used for a task of Wikipedia articles categorization. We present the Matrix’u application used for creating computational datasets ofWikipedia articles. The representations have been evaluated with SVM classifiers used for reconstruction human made categories.
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Towards Extending Wikipedia with Bidirectional Links
PublicationIn this paper, we present the results of our WikiLinks project which aims at extending current Wikipedia linkage mechanisms. Wikipedia has become recently one of the most important information sources on the Internet, which still is based on relatively simple linkage facilities. A WikiLinks system extends the Wikipedia with bidirectional links between fragments of articles. However, there were several attempts to introduce bidirectional...
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Bidirectional Fragment to Fragment Links in Wikipedia
PublicationThe paper presents a WikiLinks system that extends the Wikipedia linkage model with bidirectional links between fragments of the articles and overlapping links’ anchors. The proposed model adopts some ideas from the research conducted in a field of nonlinear, computer-aided writing, often called a hypertext. WikiLinks may be considered as a web augmentation tool but it presents a new approach to the problem that addresses the specific...
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Information Retrieval in Wikipedia with Conceptual Directions
PublicationThe paper describes our algorithm used for retrieval of textual information from Wikipedia. The experiments show that the algorithm allows to improve typical evaluation measures of retrieval quality. The improvement of the retrieval results was achieved by two phase usage approach. In first the algorithm extends the set of content that has been indexed by the specified keywords and thus increases the Recall value. Then, using the...
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Collaborative approach to WordNet and Wikipedia integration
PublicationIn this article we present a collaborative approach tocreating mappings between WordNet and Wikipedia. Wikipediaarticles have been first matched with WordNet synsets in anautomatic way. Then such associations have been evaluated andcomplemented in a collaborative way using a web application.We describe algorithms used for creating automatic mappingsas well as a system for their collaborative development. Theoutcome enables further...
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Categorization of Wikipedia articles with spectral clustering
PublicationAbstract. The article reports application of clustering algorithms for creating hierarchical groups withinWikipedia articles.We evaluate three spectral clustering algorithms based on datasets constructed with usage ofWikipedia categories. Selected algorithm has been implemented in the system that categorize Wikipedia search results in the fly.
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Towards automatic classification of Wikipedia content
PublicationArtykuł opisuje podejście do automatycznej klasyfikacji artykułów w Wikipedii. Przeanalizowane zostały reprezentacje tekstu bazujące na treści dokumentu i wzajemnych powiązaniach. Przedstawiono rezultaty zastosowania klasyfikatora SVM.
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Mining relations between wikipedia categories
PublicationOpisano metody indukcji powiązań pomiędzy kategoriami organizującymi zbiór dokumentów. Przedstawiono wyniki zastosowania proponowanego podejścia dla poprawy systemu kategorii Wikipedii.
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Exact-match Based Wikipedia-WordNet Integration
PublicationAbility to link between WordNet synsets and Wikipedia articles allows usage of those resources by computers during natural language processing. A lot of work was done in this field, however most of the approaches focus on similarity between Wikipedia articles and WordNet synsets rather than creation of perfect matches. In this paper we proposed a set of methods for automatic perfect matching generation. The proposed methods were...
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Interactive Information Retrieval Algorithm for Wikipedia Articels
PublicationThe article presents an algorithm for retrieving textual information in documents collection. The algorithm employs a category system that organizers the repository and using interaction with user improves search precision. The algorithm was implemented for simple English Wikipedia and the first evaluation results indicates the proposed method can help to retrieve information from large document repositories.
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Exact-match Based Wikipedia-WordNet Integration
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Wordventure - Developing WordNet in Wikipedia-like Style
PublicationThe article describes an approach for building WordNet semantic dictionary in a collaborative way. The idea of gathering lexical data has been proposed, as well as the system for linguistic data acquisition and management.
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Spectral Clustering Wikipedia Keyword-Based search Results
PublicationThe paper summarizes our research in the area of unsupervised categorization of Wikipedia articles. As a practical result of our research, we present an application of spectral clustering algorithm used for grouping Wikipedia search results. The main contribution of the paper is a representation method for Wikipedia articles that has been based on combination of words and links and used for categoriation of search results in this...
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Wikipedia and WordNet integration based on words co-occurrences
PublicationThe article presents a method for automatic integration of two lexical resources: semantic dictionary WordNet and electronic encyclopaedia Wikipedia. Our goal is to add automatically an semantic tags - a WordNet synset identifier to the title of the Wikipedia article. We've analyze several different ap-proaches to these problem and implement our own solution, based on word occurrences in synsets descriptions and the article body....
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Game with a Purpose for Verification of Mappings Between Wikipedia and WordNet
PublicationThe paper presents a Game with a Purpose for verification of automatically generated mappings focusing on mappings between WordNet synsets and Wikipedia articles. General description of idea standing behind the games with the purpose is given. Description of TGame system, a 2D platform mobile game with verification process included in the game-play, is provided. Additional mechanisms for anti-cheating, increasing player’s motivation...
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An Analysis of Neural Word Representations for Wikipedia Articles Classification
PublicationOne of the current popular methods of generating word representations is an approach based on the analysis of large document collections with neural networks. It creates so-called word-embeddings that attempt to learn relationships between words and encode this information in the form of a low-dimensional vector. The goal of this paper is to examine the differences between the most popular embedding models and the typical bag-of-words...
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Self–Organizing Map representation for clustering Wikipedia search results
PublicationThe article presents an approach to automated organization of textual data. The experiments have been performed on selected sub-set of Wikipedia. The Vector Space Model representation based on terms has been used to build groups of similar articles extracted from Kohonen Self-Organizing Maps with DBSCAN clustering. To warrant efficiency of the data processing, we performed linear dimensionality reduction of raw data using Principal...
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Crowdsourcing-Based Evaluation of Automatic References Between WordNet and Wikipedia
PublicationThe paper presents an approach to build references (also called mappings) between WordNet and Wikipedia. We propose four algorithms used for automatic construction of the references. Then, based on an aggregation algorithm, we produce an initial set of mappings that has been evaluated in a cooperative way. For that purpose, we implement a system for the distribution of evaluation tasks, that have been solved by the user community....
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0-step K-means for clustering Wikipedia search results
PublicationThis article describes an improvement for K-means algorithm and its application in the form of a system that clusters search results retrieved from Wikipedia. The proposed algorithm eliminates K-means isadvantages and allows one to create a cluster hierarchy. The main contributions of this paper include the ollowing: (1) The concept of an improved K-means algorithm and its application for hierarchical clustering....
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Relation-based Wikipedia Search System for Factoid Questions Answering
PublicationIn this paper we propose an alternative keyword search mechanism for Wikipedia, designed as a prototype solution towards factoid questions answering. The method considers relations between articles for finding the best matching article. Unlike the standard Wikipedia search engine and also Google engine, which search the articles content independently, requiring the entire query to be satisfied by a single article, the proposed...
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Self-Organizing Map representation for clustering Wikipedia search results
PublicationThe article presents an approach to automated organization of textual data. The experiments have been performed on selected sub-set of Wikipedia. The Vector Space Model representation based on terms has been used to build groups of similar articles extracted from Kohonen Self-Organizing Maps with DBSCAN clustering. To warrant efficiency of the data processing, we performed linear dimensionality reduction of raw data using Principal...
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Path-based methods on categorical structures for conceptual representation of wikipedia articles
PublicationMachine learning algorithms applied to text categorization mostly employ the Bag of Words (BoW) representation to describe the content of the documents. This method has been successfully used in many applications, but it is known to have several limitations. One way of improving text representation is usage of Wikipedia as the lexical knowledge base – an approach that has already shown promising results in many research studies....
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Przegląd badań na temat Wikipedii oraz z wykorzystaniem Wikipedii jako instrument badawczego
PublicationW badaniach dotychczas prowadzonych w Polsce Wikipedia była zarówno przedmiotem badań, jak i instrumentem badawczym. Badania na jej temat oraz na temat skutków społecznych jej używania prowadzili przedstawiciele nauk humanistycznych, społecznych, ekonomicznych i prawnych. Dla wielu badaczy (zwłaszcza z dziedziny informatyki) Wikipedia była instrumentem pomocnym w prowadzeniu różnorodnych analiz i dociekań naukowych. Niniejszy artykuł...
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Comparative Analysis of Text Representation Methods Using Classification
PublicationIn our work, we review and empirically evaluate five different raw methods of text representation that allow automatic processing of Wikipedia articles. The main contribution of the article—evaluation of approaches to text representation for machine learning tasks—indicates that the text representation is fundamental for achieving good categorization results. The analysis of the representation methods creates a baseline that cannot...
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Wydobywanie wiedzy z Wikipedii
PublicationWikipedia jest olbrzymim źródłem wiedzy encyklopedycznej gromadzonej przez ludzi i przeznaczonej dla ludzi. W systemach informatycznych odpowiednikiem takiego źródła wiedzy są ontologie. Ten rozdział pokazuje, w jaki sposób Wikipedia jest transformowana w ontologię i jak wydobywać z niej pojęcia, ich właściwości i relacje między nimi.
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Text classifiers for automatic articles categorization
PublicationThe article concerns the problem of automatic classification of textual content. We present selected methods for generation of documents representation and we evaluate them in classification tasks. The experiments have been performed on Wikipedia articles classified automatically to their categories made by Wikipedia editors.
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Wordventure - cooperative wordnet editor. Architecture for lexical semantic aquisition
PublicationThis article presents architecture for acquiring lexical semanticsin a collaborative approach paradigm. The system enablesfunctionality for editing semantic networks in a wikipedia-like style. The core of the system is a user-friendly interface based on interactive graph navigation.It has been used for semantic network presentation,and brings simultaneously modification functionality.
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WordVenture - COOPERATIVE WordNet EDITOR Architecture for Lexical Semantic Acquisition
PublicationThis article presents architecture for acquiring lexical semantics in a collaborative approach paradigm. The system enables functionality for editing semantic networks in a wikipedia-like style. The core of the system is a user-friendly interface based on interactive graph navigation. It has been used for semantic network presentation, and brings simultaneously modification functionality.
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Self Organizing Maps for Visualization of Categories
PublicationVisualization of Wikipedia categories using Self Organizing Mapsshows an overview of categories and their relations, helping to narrow down search domains. Selecting particular neurons this approach enables retrieval of conceptually similar categories. Evaluation of neural activations indicates that they form coherent patterns that may be useful for building user interfaces for navigation over category structures.
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Towards Increasing Density of Relations in Category Graphs
PublicationIn the chapter we propose methods for identifying new associations between Wikipedia categories. The first method is based on Bag-of-Words (BOW) representation of Wikipedia articles. Using similarity of the articles belonging to different categories allows to calculate the information about categories similarity. The second method is based on average scores given to categories while categorizing documents by our dedicated score-based...
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Metody ekstrakcji ustrukturalizowanej treści z Wikipedii
PublicationWikipedia jest od dawna przedmiotem zainteresowania badaczy. Jednym z obszarów zainteresowania jest pozyskiwanie wiedzy z treści Wikipedii a to wymaga parsowania tekstu artykułów. W tym rozdziale przedstawiono analizę porównawczą różnych możliwości parsowania treści Wikipedii, wskazując problemy, z jakimi muszą się mierzyć autorzy parserów. Dzięki temu można zrozumieć, dlaczego proces wydobywania wiedzy z Wikipedii jest trudny
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Management of Textual Data at Conceptual Level
PublicationThe article presents the approach to the management of a large repository of documents at conceptual level. We describe our approach to representing Wikipedia articles using their categories. The representation has been used to construct groups of similar articles. Proposed approach has been implemented in prototype system that allows to organize articles that are search results for a given query. Constructed clusters allow to...
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Review on Wikification methods
PublicationThe paper reviews methods on automatic annotation of texts with Wikipedia entries. The process, called Wikification aims at building references between concepts identified in the text and Wikipedia articles. Wikification finds many applications, especially in text representation, where it enables one to capture the semantic similarity of the documents. Also, it can be considered as automatic tagging of the text. We describe typical...
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Evaluation of Path Based Methods for Conceptual Representation of the Text
PublicationTypical text clustering methods use the bag of words (BoW) representation to describe content of documents. However, this method is known to have several limitations. Employing Wikipedia as the lexical knowledge base has shown an improvement of the text representation for data-mining purposes. Promising extensions of that trend employ hierarchical organization of Wikipedia category system. In this paper we propose three path-based...
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Towards Facts Extraction From Texts in Polish Language
PublicationThe Polish language differs from English in many ways. It has more complicated conjugation and declination. Because of that automatic facts extraction from texts is difficult. In this paper we present basic differences between those languages. The paper presents an algorithm for extraction of facts from articles from Polish Wikipedia. The algorithm is based on 7 proposed facts schemes that are searched for in the analyzed text....
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Dynamic Semantic Visual Information Management
PublicationDominant Internet search engines use keywords and therefore are not suited for exploration of new domains of knowledge, when the user does not know specific vocabulary. Browsing through articles in a large encyclopedia, each presenting a small fragment of knowledge, it is hard to map the whole domain, see relevant concepts and their relations. In Wikipedia for example some highly relevant articles are not linked with each other....
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Selecting Features with SVM
PublicationA common problem with feature selection is to establish how many features should be retained at least so that important information is not lost. We describe a method for choosing this number that makes use of Support Vector Machines. The method is based on controlling an angle by which the decision hyperplane is tilt due to feature selection. Experiments were performed on three text datasets generated from a Wikipedia dump. Amount...
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DBpedia As a Formal Knowledge Base – An Evaluation
PublicationDBpedia is widely used by researchers as a mean of accessing Wikipedia in a standardized way. In this paper it is characterized from the point of view of questions answering system. Simple implementation of such system is also presented. The paper also characterizes alternatives to DBpedia in form of OpenCyc and YAGO knowledge bases. A comparison between DBpedia and those knowledge bases is presented.
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Improving css-KNN Classification Performance by Shifts in Training Data
PublicationThis paper presents a new approach to improve the performance of a css-k-NN classifier for categorization of text documents. The css-k-NN classifier (i.e., a threshold-based variation of a standard k-NN classifier we proposed in [1]) is a lazy-learning instance-based classifier. It does not have parameters associated with features and/or classes of objects, that would be optimized during off-line learning. In this paper we propose...
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Automatyczna budowa taksonomii usług w oparciu o ich głosy w języku naturalnym oraz przy uzyciu zewnętrznych źródeł wiedzy
PublicationPrzedstawiono propozycję metody automatycznej budowy taksonomiiusług na podstawie ich opisów w języku naturalnym, w oparciu ometodę analizy formalnych koncepcji (FCA). Dodatkowo przedstawione rozwiązanie przewiduje możliwość skorzystania z zewnętrznych źródeł wiedzy takich jak Wikipedia, Word Net, ConceptNet lub globalnej sieci WWW w celu eliminacji problemu niepełnych danych wejściowych (ang. data sparseness).
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Cooperative Word Net Editor for Lexical Semantic Acquisition
PublicationThe article describes an approach for building Word Net semantic dictionary in a collaborative approach paradigm. The presented system system enables functionality for gathering lexical data in a Wikipedia-like style. The core of the system is a user-friendly interface based on component for interactive graph navigation. The component has been used for Word Net semantic network presentation on web page, and it brings functionalities...
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Words context analysis for improvement of information retrieval
PublicationIn the article we present an approach to improvement of retrieval informationfrom large text collections using words context vectors. The vectorshave been created analyzing English Wikipedia with Hyperspace Analogue to Language model of words similarity. For test phrases we evaluate retrieval with direct user queries as well as retrieval with context vectors of these queries. The results indicate that the proposed method can not...
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Thresholding Strategies for Large Scale Multi-Label Text Classifier
PublicationThis article presents an overview of thresholding methods for labeling objects given a list of candidate classes’ scores. These methods are essential to multi-label classification tasks, especially when there are a lot of classes which are organized in a hierarchy. Presented techniques are evaluated using the state-of-the-art dedicated classifier on medium scale text corpora extracted from Wikipedia. Obtained results show that the...
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Towards Effective Processing of Large Text Collections
PublicationIn the article we describe the approach to parallelimplementation of elementary operations for textual data categorization.In the experiments we evaluate parallel computations ofsimilarity matrices and k-means algorithm. The test datasets havebeen prepared as graphs created from Wikipedia articles relatedwith links. When we create the clustering data packages, wecompute pairs of eigenvectors and eigenvalues for visualizationsof...
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Game with a Purpose for Mappings Verification
PublicationMappings verification is a laborious task. The paper presents a Game with a Purpose based system for verification of automatically generated mappings. General description of idea standing behind the games with the purpose is given. Description of TGame system, a 2D platform mobile game with verification process included in the gameplay, is provided. Additional mechanisms for anti-cheating, increasing player’s motivation and gathering...
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External Validation Measures for Nested Clustering of Text Documents
PublicationAbstract. This article handles the problem of validating the results of nested (as opposed to "flat") clusterings. It shows that standard external validation indices used for partitioning clustering validation, like Rand statistics, Hubert Γ statistic or F-measure are not applicable in nested clustering cases. Additionally to the work, where F-measure was adopted to hierarchical classification as hF-measure, here some methods to...
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Parallel Computations of Text Similarities for Categorization Task
PublicationIn this chapter we describe the approach to parallel implementation of similarities in high dimensional spaces. The similarities computation have been used for textual data categorization. A test datasets we create from Wikipedia articles that with their hyper references formed a graph used in our experiments. The similarities based on Euclidean distance and Cosine measure have been used to process the data using k-means algorithm....
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Passing from requirements specification to class model using application domain ontology
PublicationThe quality of a classic software engineering process depends on the completeness of project documents and on the inter-phase consistency. In this paper, a method for passing from the requirement specification to the class model is proposed. First, a developer browses the text of the requirements, extracts the word sequences, and places them as terms into the glossary. Next, the internal ontology logic for the glossary needs to...
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Selection of Relevant Features for Text Classification with K-NN
PublicationIn this paper, we describe five features selection techniques used for a text classification. An information gain, independent significance feature test, chi-squared test, odds ratio test, and frequency filtering have been compared according to the text benchmarks based on Wikipedia. For each method we present the results of classification quality obtained on the test datasets using K-NN based approach. A main advantage of evaluated...