Post Covid-19 outbreak has shown a growing trend in technology adoption. Instantaneously, the research on entrepreneurship surged to shed light impact of this national economy. This aims explore papers specifically journal articles technopreneurship that were published Scopus database. 489 and 106 documents found database query extracted VOSviewer for data visualization. Key themes identified u...

Sentence retrieval is a very important part of question answering systems. Term clustering, in turn, is an effective approach for improving sentence retrieval performance: the more similar the terms in each cluster, the better the performance of the retrieval system. A key step in obtaining appropriate word clusters is accurate estimation of pairwise word similarities, based on their tendency t...

This work presents an exploratory data analysis of the syntactic distribution pre- and postverbal negation (N1 N2) in a corpus gathered from two linguistic atlases, Linguistic Atlas France (ALF) Italo-Swiss (AIS). Metadata concerning N1 N2 across dialects contexts are analyzed with r package Rbrul. Multiple logistic regression allows us to assess how independent variables affect presence/absenc...

Relationships between authors based on characteristics of published literature have been studied for decades. Author cocitation analysis using mapping techniques has been most frequently used to study how closely two authors are thought to be in intellectual space based on how members of the research community co-cite their works. Other approaches exist to study author relatedness based more di...

In this paper, we propose a novel topic model based on incorporating dictionary definitions. Traditional topic models treat words as surface strings without assuming predefined knowledge about word meaning. They infer topics only by observing surface word co-occurrence. However, the co-occurred words may not be semantically related in a manner that is relevant for topic coherence. Exploiting di...

This paper investigates a special type of recurrent expressions, lexical bundles, defined as a sequence of three or more words that co-occur frequently in a particular register (Biber et al., 1999). Considering the importance of this group of multi-word sequences in academic prose, this study explores the forms and syntactic structures of three- and four-word bundles in English abstracts writte...

The existing word representation methods mostly limit their information source to word co-occurrence statistics. In this paper, we introduce ngrams into four representation methods: SGNS, GloVe, PPMI matrix, and its SVD factorization. Comprehensive experiments are conducted on word analogy and similarity tasks. The results show that improved word representations are learned from ngram cooccurre...

To comprehend language, listeners need to encode the relationship between words within sentences. This entails categorizing words into their appropriate word classes. Function words, consistently preceding words from specific categories (e.g., the ballNOUN, I speakVERB), provide invaluable information for this task, and children's sensitivity to such adjacent relationships develops early on in ...

purpose: this study aimed to measure the information load of words in farsi scientific texts and determine the relationship between some properties of the words and information load of the texts based on shannon entropy. methodology: the study was conducted based on the content analysis of a number of 320 articles that were published in scientific-research iranian journals in 2009. and the arti...