Web search has become one of the most important fields of research around the world. They are many reasonsincluding: the fast-growing nature of information sources; the search necessity for ...information closer to specificuser requirements; the need to reduce search time; and the desire to take into account the semantics of terms usedwhen doing search queries. This paper shows a semantic meta-web search model called XGhobi which uses indexedresources by Google, Yahoo! and Bing. The XGhobi engine combines a general taxonomy of knowledge, a generaldomain ontology –WordNet-, a set of specific domain ontologies, and user profile management to improve therelevance of recovered documents in both English and Spanish. A detailed description of the meta-web searchengine’s components, some user interfaces and its results and its assessments are shown. The assessment covers theobtained precision on tests done by users.
La búsqueda web en los últimos años se ha convertido en una de las áreas de investigación más importantes delmundo, debido entre otras cosas: al crecimiento acelerado de las fuentes de información, a la necesidad de contar coninformación más relevante a los requerimientos específicos de cada usuario, a la exploración de menores tiempos debúsqueda y a la falta de usar la semántica de los términos implicados en las consultas. En este artículo se presentael modelo de un meta-buscador (usa los recursos indexados por Google, Yahoo! y Bing) web semántico llamadoXGhobi, que incorpora una taxonomía general de conocimiento, una ontología de dominio general (WordNet), unconjunto de ontologías de dominio específico y el perfil de los usuarios para mejorar la relevancia de los documentosrecuperados tanto en inglés como en español. Se describe en detalle los componentes del meta-buscador, algunasinterfaces de usuario y los resultados de su evaluación. La evaluación del sistema muestra la precisión obtenida enpruebas realizadas con usuarios.
To make the word similarity calculated results more reasonable and accurate, a new word similarity algorithm is proposed. It uses HowNet primitive hierarchical tree structure, and calculates the two ...primitives’ distance with the method computing WordNet node distance which considers the tree depth, density, path and connecting intensity, etc. Moreover, algorithm also improves the method that distance into similarity. Finally, this algorithm is compared with related algorithms through experiment. The results show that the proposed algorithm effectively improves the precision and accuracy of word similarity calculation.
Two novel techniques based on term expansion for domain-specific Word Sense Disambiguation are presented in this paper. A list of terms correlated with the ambiguous word is obtained by means of ...correlation methods such as Pointwise Mutual Information and Chi-square. The list of correlated terms is used for expanding the context in which an ambiguous word occurs, thus leading to a better number of terms which may be further used for determining the correct sense of the target ambiguous word. The proposed method has been tested in domain-specific corpora (Finance and Sports) and in one balanced corpus, the British National Corpus (BNC). The obtained results for domain-specific corpora are competitive (Finance) and ever better (Sports and BNC) than those reported in previous works.
The paper describes a semantic-based system for e-learning platforms, designed to automate some highly time-consuming activities for the account of the cognitive process actors. To this end the ...system helps the instructor organize the support material for Learning Objects and guides the student in learning the structure of specific knowledge domain. Concerning the first of these aspects, the teacher is required only to indicate the resources in digital format (e-books, documents, Web pages) strictly connected to the lesson topic delivered in a structured way. At the student level, an interaction with a chatbot was analyzed in order to make the research and exploration of content more interactive. The virtual assistant guides the student in understanding structured contexts at different levels of detail (book, chapter, paragraph, sentence and phrase) and their mutual logical organization. The knowledge base was developed on the basis of the Semantic Web paradigm and uses WordNet as reference ontology. A prototype system is currently under test and evaluation at the AeFLab Laboratory of the Politecnico di Bari.
This paper deals with certain morphosemantic relations between Croatian verbs and discusses their inclusion in Croatian WordNet. The morphosemantic relations in question are the semantic relations ...between unprefixed infinitives and their prefixed derivatives. We introduce the criteria for the division of aspectual pairs and further discuss verb prefixation which results in combinations of prefixes and base forms that can vary in terms of meaning from compositional to completely idiosyncratic. The focus is on the regularities in semantic modifications of base forms modified by one prefix. The aim of this procedure is to establish a set of morphosemantic relations based on regular or reoccuring meaning alternations.
It has long been a dream to have available a single, centralized, semantic thesaurus or terminology taxonomy to support research in a variety of fields. Much human and computational effort has gone ...into constructing such resources, including the original WordNet and subsequent wordnets in various languages. To produce such resources one has to overcome well-known problems in achieving both wide coverage and internal consistency within a single wordnet and across many wordnets. In particular, one has to ensure that alternative valid taxonomizations covering the same basic terms are recognized and treated appropriately. In this paper we describe a pipeline of new, powerful, minimally supervised, automated algorithms that can be used to construct terminology taxonomies and wordnets, in various languages, by harvesting large amounts of online domain-specific or general text. We illustrate the effectiveness of the algorithms both to build localized, domain-specific wordnets and to highlight and investigate certain deeper ontological problems such as parallel generalization hierarchies. We show shortcomings and gaps in the manually-constructed English WordNet in various domains.
A Survey on Semantic Similarity P., Sunilkumar; Shaji, Athira P.
2019 International Conference on Advances in Computing, Communication and Control (ICAC3),
2019-Dec.
Conference Proceeding
This paper provides a survey of semantic similarity of text documents. Semantic Similarity is an important task in Natural Language Processing (NLP). It is widely used for information retrieval, text ...classification, question answering, and plagiarism detection. This survey will classify different types of semantic similarity approaches such as corpus-based, knowledge-based and string-based. Various papers are reviewed and prepared performance analysis in this survey.
The explosion of information in the World Wide Web is overwhelming for readers with limitless information. Large internet articles or journals are often cumbersome to read as well as comprehend. More ...often than not, readers are immersed in a pool of information with limited time to assimilate all of the articles. As technology advances, it becomes more convenient to access information on-the-go, i.e., portability of information by utilizing mobile devices. In this research, a semantic and syntatic based summarization is implemented in a text summarizer to solve the information overload problem whilst providing a more coherent summary. The objective is to integrate WordNet into the proposed system aka TextSumIt which condenses lengthy documents into summarized text. The empirical experiments show that it produces satisfactory preliminary results on Android mobile phones.
This paper provides a deduction-based approach for automatically classifying compound-internal relations in GermaNet, the German version of the Princeton WordNet for English. More specifically, ...meronymic relations between simplex and compound nouns provide the necessary input to the deduction patterns that involve different types of compound-internal relations. The scope of these deductions extends to all four meronymic relations modeled in version 6.0 of GermaNet: component, member, substance, and portion. This deduction-based approach provides an effective method for automatically enriching the set of semantic relations included in GermaNet.
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