This paper presents the results of a bibliometric analysis published academic research on innovation in hotels. In particular, it aims to analyze conceptual structure field, covering period until October 2020, and predict emerging trends. approach provides an exhaustive 334 papers collected from Scopus database. Co-word used identify reveals four clusters: (1) technological innovation, (2) inno...

The rapid development of the Internet and World Wide Web has caused some critical problem for information retrieval. Researchers have made several attempts to solve these problems. Thesauri and subject heading lists as traditional information retrieval tools have been criticised for their efficiency to tackle these newly emerging problems. This paper proposes an information retrieval tool gener...

Abstract Using geographic information systems (GIS) widely for dealing with transportation problems (is well-known as GIS-T), has made it nessasary researchers to discover the current state-of-the-art and predict trends of future research. This paper aims contribute a better understanding GIS-T research area from longitudinal perspective, over period 2008–2019. A co-word analysis was used illus...

Offering reference for sustainable researches of psychological warning field by analyzing hotspots in it the latest decade. 589 literatures relevant to conformed standard, were extracted keywords. Cooccurrence matrix and lexical exported using python software, correlations among high frequency keywords received combination between social network semantic which also drew graph. The hierarchical ...

Cross-language information retrieval (CLIR) and multilingual information retrieval (MLIR) techniques have been widely studied, but they are not often applied to and evaluated for Web applications. In this paper, we present our research in developing and evaluating a multilingual English-Chinese Web portal in the business domain. A dictionary-based approach has been adopted that combines phrasal...

Topic models learn topics base on the amount of the word co-occurrence in the documents. The word co-occurrence is a degree which describes how often the two words appear together. BTM, discovers topics from bi-terms in the whole corpus to overcome the lack of local word co-occurrence information. However, BTM will make the common words be performed excessively because BTM identifies the word c...

Latent Semantic Analysis (LSA) and Word Space are two semantic models derived from the vector space model of distributional semantics that have been used successfully in word-sense disambiguation and discrimination. LSA can represent word types and word tokens in context by means of a single matrix factorised by Singular Value Decomposition (SVD). Word Space is able to represent types via word ...

The co-word problem of a group G generated by a set X is defined as the set of words in X which do not represent 1 in G. We introduce a new method to decide if a permutation group has context-free co-word problem. We use this method to show, that the Higman-Thompson groups, and therefore the Houghton groups, have context-free co-word problem. We also give some examples of groups, that even have...