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    Wyświetlanie 1-6 z 6
    Tytuł:
    Experimental Comparison of Pre-Trained Word Embedding Vectors of Word2Vec, Glove, FastText for Word Level Semantic Text Similarity Measurement in Turkish
    Autorzy:
    Tulu, Cagatay Neftali
    Powiązania:
    https://bibliotekanauki.pl/articles/2201815.pdf
    Data publikacji:
    2022
    Wydawca:
    Stowarzyszenie Inżynierów i Techników Mechaników Polskich
    Tematy:
    semantic word similarity
    word embeddings
    NLP
    Turkish NLP
    natural language processing
    Opis:
    This study aims to evaluate experimentally the word vectors produced by three widely used embedding methods for the word-level semantic text similarity in Turkish. Three benchmark datasets SimTurk, AnlamVer, and RG65_Turkce are used in this study to evaluate the word embedding vectors produced by three different methods namely Word2Vec, Glove, and FastText. As a result of the comparative analysis, Turkish word vectors produced with Glove and FastText gained better correlation in the word level semantic similarity. It is also found that The Turkish word coverage of FastText is ahead of the other two methods because the limited number of Out of Vocabulary (OOV) words have been observed in the experiments conducted for FastText. Another observation is that FastText and Glove vectors showed great success in terms of Spearman correlation value in the SimTurk and AnlamVer datasets both of which are purely prepared and evaluated by local Turkish individuals. This is another indicator showing that these aforementioned datasets are better representing the Turkish language in terms of morphology and inflections.
    Źródło:
    Advances in Science and Technology. Research Journal; 2022, 16, 4; 147--156
    2299-8624
    Pojawia się w:
    Advances in Science and Technology. Research Journal
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Extraction of Polish noun senses from large corpora by means of clustering
    Autorzy:
    Broda, B.
    Piasecki, M.
    Szpakowicz, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/969804.pdf
    Data publikacji:
    2010
    Wydawca:
    Polska Akademia Nauk. Instytut Badań Systemowych PAN
    Tematy:
    corpus linguistics
    semantic similarity
    Polish nouns
    word clustering
    Clustering by Committee
    co-occurrence retrieval models
    rank weight function
    Polish WordNet
    WordNet-based synonymy test
    document clustering
    keywords extraction
    Opis:
    We investigate two methods of identifying noun senses, based on clustering of lemmas and of documents. We have adapted to Polish the well-known algorithm of Clustering by Committee, and tested it on very large Polish corpora. The evaluation by means of a WordNet-based synonymy test used Polish wordnet (plWordNet 1.0). Various clustering algorithms were analysed for the needs of extraction of document clusters as indicators of the senses of words which occur in them. The two approaches to wordsense identification have been compared, and conclusions drawn.
    Źródło:
    Control and Cybernetics; 2010, 39, 2; 401-420
    0324-8569
    Pojawia się w:
    Control and Cybernetics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Cloud computing migration barriers and advantages in manufacturing – an analysis of ambiguity and dependences in the assessment criteria
    Bariery i korzyści migracji do chmury obliczeniowej w przedsiębiorstwach przemysłowych – analiza niejednoznaczności i związków między kryteriami oceny
    Autorzy:
    Bartkiewicz, Witold
    Gontar, Zbigniew
    Powiązania:
    https://bibliotekanauki.pl/articles/425213.pdf
    Data publikacji:
    2018
    Wydawca:
    Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
    Tematy:
    cloud computing
    association mining
    similarity based semantic clustering
    Opis:
    There is still many misunderstandings associated with the assessment of the barriers encountered in the process of IT solutions migration to the computational cloud and the benefits to be expected. The purpose of this paper is to organize the criteria used in this field, to analyze the dependencies between them. This will allow us to better understand the problem of migration to the cloud and to improve the decision-making processes related to it. A comprehensive survey was carried out, covering about 400 manufacturing enterprises in Poland using cloud-based IT solutions in various areas. The elements of the study were questions about the barriers and benefits encountered in this process. The paper analyzes the relationships between the obtained categories using diverse data mining methods: association rules mining and hierarchical agglomerative clustering. The obtained results allow to identify the conceptual structure and build a model of relationships inside the problem.
    Źródło:
    Econometrics. Ekonometria. Advances in Applied Data Analytics; 2018, 22, 3; 41-54
    1507-3866
    Pojawia się w:
    Econometrics. Ekonometria. Advances in Applied Data Analytics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The logic and linguistic model for automatic extraction of collocation similarity
    Autorzy:
    Khairova, N.
    Petrasova, S.
    Gautam, A. P. S.
    Powiązania:
    https://bibliotekanauki.pl/articles/411457.pdf
    Data publikacji:
    2015
    Wydawca:
    Polska Akademia Nauk. Oddział w Lublinie PAN
    Tematy:
    automatic extraction
    identification of collocation similarity
    finite predicates algebra
    logicalalgebraic equations
    grammatical and semantic features
    Opis:
    The article discusses the process of automatic identification of collocation similarity. The semantic analysis is one of the most advanced as well as the most difficult NLP task. The main problem of semantic processing is the determination of polysemy and synonymy of linguistic units. In addition, the task becomes complicated in case of word collocations. The paper suggests a logical and linguistic model for automatic determining semantic similarity between colocations in Ukraine and English languages. The proposed model formalizes semantic equivalence of collocations by means of semantic and grammatical characteristics of collocates. The basic idea of this approach is that morphological, syntactic and semantic characteristics of lexical units are to be taken into account for the identification of collocation similarity. Basic mathematical means of our model are logical-algebraic equations of the finite predicates algebra. Verb-noun and noun-adjective collocations in Ukrainian and English languages consist of words belonged to main parts of speech. These collocations are examined in the model. The model allows extracting semantically equivalent collocations from semi-structured and non-structured texts. Implementations of the model will allow to automatically recognize semantically equivalent collocations. Usage of the model allows increasing the effectiveness of natural language processing tasks such as information extraction, ontology generation, sentyment analysis and some others.
    Źródło:
    ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes; 2015, 4, 4; 43-48
    2084-5715
    Pojawia się w:
    ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Distinguishing between paradigmatic semantic relations across word classes : human ratings and distributional similarity
    Autorzy:
    Schulte im Walde, Sabine
    Powiązania:
    https://bibliotekanauki.pl/articles/1429743.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Instytut Podstaw Informatyki PAN
    Tematy:
    semantic relations
    human ratings
    distributional semantics
    automatic classification
    Opis:
    This article explores the distinction between paradigmatic semantic relations, both from a cognitive and a computational linguistic perspective. Focusing on an existing dataset of German synonyms, antonyms and hypernyms across the word classes of nouns, verbs and adjectives, we assess human ratings and a supervised classification model using window-based and pattern-based distributional vector spaces. Both perspectives suggest differences in relation distinction across word classes, but easy vs. difficult class-relation combinations differ, exhibiting stronger ties between ease and naturalness of class-dependent relations for humans than for computational models. In addition, we demonstrate that distributional information is indeed a difficult starting point for distinguishing between paradigmatic relations but that even a simple classification model is able to manage this task. The fact that the most salient vector spaces and their success vary across word classes and paradigmatic relations suggests that combining feature types for relation distinction is better than applying them in isolation.
    Źródło:
    Journal of Language Modelling; 2020, 8, 1; 53-101
    2299-856X
    2299-8470
    Pojawia się w:
    Journal of Language Modelling
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The method of a two-level text-meaning similarity approximation of the customers’ opinions
    Metoda dwupoziomowego przybliżonego obliczenia podobieństwa znaczenia tekstów opinii klientów
    Autorzy:
    Rizun, Nina
    Kapłański, Paweł
    Taranenko, Yurii
    Powiązania:
    https://bibliotekanauki.pl/articles/590266.pdf
    Data publikacji:
    2016
    Wydawca:
    Uniwersytet Ekonomiczny w Katowicach
    Tematy:
    Latent Semantic Analysis
    Social Network Analysis
    Text-meaning
    Analiza sieci społecznych
    Ukryta analiza semantyczna
    Znaczenie tekstu
    Opis:
    The method of two-level text-meaning similarity approximation, consisting in the implementation of the classification of the stages of text opinions of customers and identifying their rank quality level was developed. Proposed and proved the significance of major hypotheses, put as the basis of the developed methodology, notably about the significance of suggestions about the existence of analogies between mathematical bases of the theory of Latent Semantic Analysis, based on the analysis of semantic relationship between the variables and degree of participation of the document or term in the corresponding concept of the document data, and instruments of the theory of Social Network Analysis, directed at revealing the features of objects on the basis of information about structure and strength of their interaction. The Contextual Cluster Structure, as well as Quantitative Ranking evaluation for interpreting the quality level of estimated customers’ opinion has formed.
    Opracowano metodę dwupoziomowej aproksymacji podobieństwa – metodę przetwarzania tekstu, którą zastosowano w problemie klasyfikacji oraz do określania poziomu jakości klientów. Posługując się zaproponowaną w artykule metodyką, udowodniono istotność głównych hipotez, w szczególności hipotezy o istnieniu analogii pomiędzy podstawami matematycznymi LSA (ang. Latent Semantic Analysis), bazującej na analizie relacji semantycznej związku między stopniem udziału analogicznych pojęć w zbiorze dokumentów a narzędziami teorii analizy sieci społecznych (ang. Social Network Analysis), która z kolei odsłaniania cechy obiektów na podstawie informacji na temat struktury ich wzajemnych powiązań. Z połączenia powyższych metod wyłoniła się struktura klastra kontekstu, dająca ocenę ilościową na potrzeby ranking poziomu jakości opinii szacowanych klientów.
    Źródło:
    Studia Ekonomiczne; 2016, 296; 64-85
    2083-8611
    Pojawia się w:
    Studia Ekonomiczne
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-6 z 6

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