Based on the relevant theories of social network research, this research uses CiteSpace software, taking literature job crafting published in web science core corpus database 2000-2019 as object. Word analysis, cluster analysis and other methods study interpret 441 documents data, draw a cooperative map authors field crafting, knowledge maps highyielding countries, co-word to reflect current st...

We present a scalable approach to automatically discovering particular objects (as opposed to object categories) from a set of images. The basic idea is to search for local image features that consistently appear in the same images under the assumption that such co-occurring features underlie the same object. We first represent each image in the set as a set of visual words (vector quantized lo...

In this paper, we will show that the performance of vector-based semantic analysis can be improved by considering basic linguistic structures in the data— e.g. morphology. For this purpose, we have used a new method for vector-based semantic analysis that computes semantic word vectors based on distributed representations by means of random labeling of words in narrow context windows. This form...

Purpose – The co-word analysis method is commonly used to cluster-related keywords into the same keyword domain. In other words, traditional co-word analysis cannot cluster the same keywords into more than one keyword domain, and disregards the multi-domain property of keywords. The purpose of this paper is to propose an innovative keyword co-citation approach called “Complete Keyword Pair (CKP...

In this paper we present an analysis of the academic landscape of games research from the last 15 years. We employed a data driven approach utilizing co-word and co-venue analysis on 48 core venues to identify 20 major research themes and 7 distinct communities, with a total of 8,207 articles and 21,552 unique keywords being analyzed. Strategic diagrams and network maps are applied to visualize...

We present a novel approach to mine word similarity in Textual Case Based Reasoning. We exploit indirect associations of words, in addition to direct ones for estimating their similarity. If word A co-occurs with word B, we say A and B share a first order association between them. If A co-occurs with B in some documents, and B with C in some others, then A and C are said to share a second order...

Word co-occurrence graphs have been used in computational linguistics mainly for word sense disambiguation and induction, but until very recently, not for the extraction of hypernymy relations, where the methodology most often applied is the use of lexico-syntactic patterns. In this paper, we show that it is possible to use word co-occurrence statistics to extract IS-A relations between entitie...

In recent years, social entrepreneurship has received an increasing attention from the academic community. Social is a topic related to various areas such as economics, management, education, sociology, psychology, and it not surprising that issues are always debated with definitions, methods, approaches. This study aims establish networks maps in based on systematic review of 1361 publications...

A relaxation-based algorithm is proposed that improves the performance of a text recognition technique by propagating the in uence of word collocation statistics. Word collocation refers to the likelihood that two words co-occur within a xed distance of one another. For example, in a story about water transportation, it is highly likely that the word \river" will occur within ten words on eithe...

A relaxation-based algorithnl is proposed that improves the performance of a text recognition technique by propagating the influence of word collocation statistics. Word collocation refers to the likelihood that two words co-occur within a fixed distance of one another. For example, in a story about water transportation, it is highly likely that the word "river" will occur within ten words on e...