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Lexical databases are powerful and easily expandable learning tools in the field of terminology learning. Their usage can provide students with learning experiences in a friendly way, providing access to a variety of sources and information in authentic linguistic environments. This paper describes the design and implementation of a lexical database as a software application of the technological field of Computational Lexicography. The original purpose of creating such a tool was to facilitate the learning of technical terminology of the scientific field of Computational Linguistics, in which the phenomenon of polysemy often occurs, namely that the same term has at least two different meanings. This phenomenon is due both to the translation of English terms into the Greek language and to the combination of different disciplines (Informatics, Mathematics and Linguistics) in the same field of applications. [ABSTRACT FROM AUTHOR]

In this article, we present StimulStat - a lexical database for the Russian language in the form of a web application. The database contains more than 52,000 of the most frequent Russian lemmas and more than 1.7 million word forms derived from them. These lemmas and forms are characterized according to more than 70 properties that were demonstrated to be relevant for psycholinguistic research, including frequency, length, phonological and grammatical properties, orthographic and phonological neighborhood frequency and size, grammatical ambiguity, homonymy and polysemy. Some properties were retrieved from various dictionaries and are presented collectively in a searchable form for the first time, the others were computed specifically for the database. The database can be accessed freely at http://stimul.cognitivestudies.ru. [ABSTRACT FROM AUTHOR]

We present the Chinese Lexical Database (CLD): a large-scale lexical database for simplified Chinese. The CLD provides a wealth of lexical information for 3913 one-character words, 34,233 two-character words, 7143 three-character words, and 3355 four-character words, and is publicly available through http://www.chineselexicaldatabase.com. For each of the 48,644 words in the CLD, we provide a wide range of categorical predictors, as well as an extensive set of frequency measures, complexity measures, neighborhood density measures, orthography-phonology consistency measures, and information-theoretic measures. We evaluate the explanatory power of the lexical variables in the CLD in the context of experimental data through analyses of lexical decision latencies for one-character, two-character, three-character and four-character words, as well as word naming latencies for one-character and two-character words. The results of these analyses are discussed. [ABSTRACT FROM AUTHOR]

Public textual cyberbullying has become one of the most prevalent issues associated with online safety of young people, particularly on social networks. To address this issue, we argue that the boundaries of what constitutes public textual cyberbullying needs to be first identified and a corresponding linguistically motivated definition needs to be advanced. Thus, we propose a definition of public textual cyberbullying that contains three necessary and sufficient elements: the personal marker, the dysphemistic element and the cyberbullying link between the previous two elements. Subsequently, we argue that one of the cornerstones in the overall process of mitigating the effects of cyberbullying is the design of a cyberbullying lexical database that specifies what linguistic and cyberbullying specific information is relevant to the detection process. In this vein, we propose a novel cyberbullying lexical database based on the definition of public textual cyberbullying. The overall architecture of our cyberbullying lexical database is determined semantically, and, in order to facilitate cyberbullying detection, the lexical entry encapsulates two new semantic dimensions that are derived from our definition: cyberbullying function and cyberbullying referential domain. In addition, the lexical entry encapsulates other semantic and syntactic information, such as sense and syntactic category, information that, not only aids the process of detection, but also allows us to expand the cyberbullying database using WordNet (Miller, 1993).

This study concerns the impact of the collocation/phraseme disambiguation component within the complex system of the rule-based morphological disambiguation of Czech. This system constitutes one of the two main disambiguation subsystems that are responsible for the morphological disambiguation of the corpora of synchronic Czech within the Czech National Corpus project. We will show that although the part of texts constituted by collocations/phrasemes (generally multiword expressions - MWEs) is relatively small and consequently the errorfree morphological disambiguation of MWEs covers only a small portion of textual material, such perfectly disambiguated fragments in sentences help to improve the disambiguation of the rest, non-MWE part of sentences. [ABSTRACT FROM AUTHOR]

Plagiarism takes place when we use any person's work without giving due acknowledgment. There are several fields where the text similarity is involved like web document retrieval, information mining, and searching related articles. Several approaches have been introduced for detecting plagiarism in the text documents based on the syntactic structure of the text, string similarity, fingerprinting, semantic meaning underlying the text, etc. The basic limitation of plagiarism detection systems these days is that they fail to detect tough cases of plagiarism. The proposed plagiarism detection approach is the hybrid of semantic and syntactic similarity between the text documents. This novel approach exploits linguistic information sources non-linearly using the lexical database for finding the relatedness between text documents. The proposed approach uses semantic knowledge to perform cognitive-inspired computing. The framework is capable of detecting intelligent plagiarism cases like a verbatim copy, paraphrasing, rewording in a sentence, and sentence transformation. The approach has been evaluated on the standard PAN-PC-11 dataset. The experiments show that our technique has outperformed other strong baseline techniques in terms of precision, recall, F-measure, and plagiarism detection (PlagDet) score. [ABSTRACT FROM AUTHOR]

This article presents K-SPAN (Korean Surface Phonetics and Neighborhoods), a database of surface phonetic forms and several measures of phonological neighborhood density for 63,836 Korean words. Currently publicly available Korean corpora are limited by the fact that they only provide orthographic representations in Hangeul, which is problematic since phonetic forms in Korean cannot be reliably predicted from orthographic forms. We describe the method used to derive the surface phonetic forms from a publicly available orthographic corpus of Korean, and report on several statistics calculated using this database; namely, segment unigram frequencies, which are compared to previously reported results, along with segment-based and syllable-based neighborhood density statistics for three types of representation: an “orthographic” form, which is a quasi-phonological representation, a “conservative” form, which maintains all known contrasts, and a “modern” form, which represents the pronunciation of contemporary Seoul Korean. These representations are rendered in an ASCIIencoded scheme, which allows users to query the corpus without having to read Korean orthography, and permits the calculation of a wide range of phonological measures. [ABSTRACT FROM AUTHOR]

Public textual cyberbullying has become one of the most prevalent issues associated with online safety of young people, particularly on social networks. To address this issue, we argue that the boundaries of what constitutes public textual cyberbullying needs to be first identified and a corresponding linguistically motivated definition needs to be advanced. Thus, we propose a definition of public textual cyberbullying that contains three necessary and sufficient elements: the personal marker, the dysphemistic element and the cyberbullying link between the previous two elements. Subsequently, we argue that one of the cornerstones in the overall process of mitigating the effects of cyberbullying is the design of a cyberbullying lexical database that specifies what linguistic and cyberbullying specific information is relevant to the detection process. In this vein, we propose a novel cyberbullying lexical database based on the definition of public textual cyberbullying. The overall architecture of our cyberbullying lexical database is determined semantically, and, in order to facilitate cyberbullying detection, the lexical entry encapsulates two new semantic dimensions that are derived from our definition: cyberbullying function and cyberbullying referential domain. In addition, the lexical entry encapsulates other information, such as sense and syntactic category, information that, not only aids the process of detection, but also allows us to expand the cyberbullying database using WordNet (Miller, 1993).semantic and syntactic [ABSTRACT FROM AUTHOR]

ASL-LEX is a lexical database that catalogues information about nearly 1,000 signs in American Sign Language (ASL). It includes the following information: subjective frequency ratings from 25-31 deaf signers, iconicity ratings from 21-37 hearing non-signers, videoclip duration, sign length (onset and offset), grammatical class, and whether the sign is initialized, a fingerspelled loan sign, or a compound. Information about English translations is available for a subset of signs (e.g., alternate translations, translation consistency). In addition, phonological properties (sign type, selected fingers, flexion, major and minor location, and movement) were coded and used to generate sub-lexical frequency and neighborhood density estimates. ASL-LEX is intended for use by researchers, educators, and students who are interested in the properties of the ASL lexicon. An interactive website where the database can be browsed and downloaded is available at . [ABSTRACT FROM AUTHOR]

Similarity calculation between business process models has an important role in managing repository of business process model. One of its uses is to facilitate the searching process of models in the repository. Business process similarity is closely related to semantic string similarity. Semantic string similarity is usually performed by utilizing a lexical database such as WordNet to find the semantic meaning of the word. The activity name of the business process uses terms that specifically related to the business field. However, most of the terms in business domain are not available in WordNet. This case would decrease the semantic analysis quality of business process model. Therefore, this study would try to improve semantic analysis of business process model. We present a new lexical database called BBabelNet. B-BabelNet is a lexical database built by using the same method in BabelNet. We attempt to map the Wikipedia page to WordNet database but only focus on the word related to the domain of business. Also, to enrich the vocabulary in the business domain, we also use terms in the business-specific online dictionary (businessdictionary.com). We utilize this database to do word sense disambiguation process on business process model activity’s terms. The result from this study shows that the database can increase the accuracy of the word sense disambiguation process especially in particular terms related to the business and industrial domains. [ABSTRACT FROM AUTHOR]

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