scholarly journals Perception of Leisure Agricultural Tourism Image Based on Wed Text Analysis: Case of Yearning Tea Plantation

2021 ◽  
Vol 235 ◽  
pp. 02013
Author(s):  
Mufeng Chen
Keyword(s):  
Text Analysis ◽  
Online Review ◽  
Mining System ◽  
Tea Plantation ◽  
Consumption Decisions ◽  
Scenic Spot ◽  
Content Mining ◽  
Tourism Image ◽  
Agricultural Tourism ◽  
Important Basis

With the in-depth development of online tourism platforms, the online review of products in scenic spots has become an important basis for tourism consumption decisions. Through data mining and analysis of the online review of products in scenic spots, the tourism image perceived by tourists has become an important way to study the tourism image of scenic spots. Taking the Yearning Tea Plantation as an example, the word frequency and the content of tourism image attributes were analyzed by using the ROST CM6 content mining system software to comment on the online tourism platform for the sample of tourists, to understand the tourists’ perception of the tourism image of the Yearning Tea Plantation, and to provide the basis for the improvement and improvement of the tourism image of the leisure agriculture scenic spot.

World Wide Web Usage Mining

2011 ◽  
pp. 1242-1248 ◽  
Author(s):  
Wen-Chen Hu ◽  
Hung-Jen Yang ◽  
Chung-wei Lee ◽  
Jyh-haw Yeh
Keyword(s):  
Data Mining ◽  
World Wide Web ◽  
World Wide ◽  
Data Gathering ◽  
Web Usage Mining ◽  
Web Data ◽  
Mining System ◽  
Data Mining Techniques ◽  
Web Usage ◽  
Content Mining

World Wide Web data mining includes content mining, hyperlink structure mining, and usage mining. All three approaches attempt to extract knowledge from the Web, produce some useful results from the knowledge extracted, and apply the results to certain real-world problems. The first two apply the data mining techniques to Web page contents and hyperlink structures, respectively. The third approach, Web usage mining (the theme of this article), is the application of data mining techniques to the usage logs of large Web data repositories in order to produce results that can be applied to many practical subjects, such as improving Web sites/pages, making additional topic or product recommendations, user/customer behavior studies, and so forth. This article provides a survey and analysis of current Web usage mining technologies and systems. A Web usage mining system must be able to perform five major functions: (i) data gathering, (ii) data preparation, (iii) navigation pattern discovery, (iv) pattern analysis and visualization, and (v) pattern applications. Many Web usage mining technologies have been proposed, and each technology employs a different approach. This article first describes a generalized Web usage mining system, which includes five individual functions. Each system function is then explained and analyzed in detail. Related surveys of Web usage mining techniques also can be found in Hu, et al. (2003) and Kosala and Blockeel (2000).

scholarly journals Big data gets big help: Law and policy literacies for text data mining

2020 ◽  
Vol 81 (4) ◽  
pp. 193
Author(s):  
Kyle Courtney ◽  
Rachael Samberg ◽  
Timothy Vollmer
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Text Analysis ◽  
Digital Content ◽  
Text Data ◽  
Text Data Mining ◽  
Large Sets ◽  
Law And Policy ◽  
Content Mining ◽  
Manual Review

A wealth of digital texts and the proliferation of automated research methodologies enable researchers to analyze large sets of data at a speed that would be impossible to achieve through manual review. When researchers use these automated techniques and methods for identifying, extracting, and analyzing patterns, trends, and relationships across large volumes of un- or thinly structured digital content, they are applying a methodology called text data mining or TDM. TDM is also referred to, with slightly different emphases, as “computational text analysis” or “content mining.”

Text analysis and knowledge mining system

2001 ◽  
Vol 40 (4) ◽  
pp. 967-984 ◽  
Author(s):  
T. Nasukawa ◽  
T. Nagano
Keyword(s):  
Text Analysis ◽  
Mining System ◽  
Knowledge Mining

scholarly journals Research Progress of Online Review Content Based on Interpretation Level Theory

2021 ◽  
Vol 251 ◽  
pp. 03092
Author(s):  
Xu Yaping ◽  
Liang Qingyu
Keyword(s):  
Purchase Intention ◽  
Information Quality ◽  
Information Dissemination ◽  
Online Reviews ◽  
Review Literature ◽  
Research Progress ◽  
Online Review ◽  
Future Research ◽  
The Impact ◽  
Important Basis

Online reviews have become the main method of information dissemination, an important factor in consumer purchase decisions, and an important basis for merchants to improve their services. It has attracted the attention of scholars. The application of explanation level theory in consumer behavior research has begun to show an increasing trend. After sorting out the existing literature, it is found that the online review literature based on the interpretation level theory mainly studies the impact on consumers’ purchase intention from the three perspectives of reviewers, review content and review readers. Among them, the content of comments is mostly discussed in terms of comment type and information quality, but it has not been systematically summarized. Using the literature review method, based on the interpretation level theory, the review type, information quality, interpretation type and perceived similarity are analyzed from the perspective of review content, and the existing literature is sorted in order to provide references for future research.

scholarly journals Shifting moods on Sina Weibo: The first 12 weeks of COVID-19 in Wuhan

2021 ◽  
pp. 146144482110588
Author(s):  
Peng Zheng ◽  
Paul C Adams ◽  
Jiejie Wang
Keyword(s):  
Social Media ◽  
Social Life ◽  
Mining System ◽  
Theoretical Understanding ◽  
Policy Makers ◽  
Sina Weibo ◽  
University Of Technology ◽  
Content Mining ◽  
Novel Coronavirus ◽  
Relative Prevalence

Better understanding of social media uses in crisis situations can help improve disaster management by policy-makers, organizations, businesses, and members of the public. It can also build theoretical understanding of how social life and citizenship incorporate social media usage. This study tracks the evolution of public sentiment in Wuhan, China, during the first 12 weeks after the identification of COVID-19 on the Chinese microblogging platform Sina Weibo. Data consist of 133,079 original Sina Weibo posts dealing with the novel coronavirus. The relative prevalence of eight different emotion groups is traced longitudinally using the ROST Content Mining System and the Emotion Vocabulary of Dalian University of Technology. The study finds a progression from confusion/fear, to disappointment/frustration, to depression/anxiety, then finally to happiness/gratitude. It argues that this progression indexes the changing affective energies of digital medical citizenship, which in turn indicates the context for intervention in future crises.

My-music my-self

2015 ◽  
Vol 18 (1) ◽  
pp. 145-160 ◽  
Author(s):  
Luke Greenacre ◽  
Lynne Freeman ◽  
Jared Filby ◽  
Taryn Ostrovsky
Keyword(s):  
Musical Theatre ◽  
The Self ◽  
Extended Model ◽  
Extended Self ◽  
Content Type ◽  
Consumption Decisions ◽  
Consumption Choices ◽  
Entertainment Products ◽  
Depth Interviews ◽  
Important Basis

Purpose – The purpose of this article is to use an extended model of self to understand the consumption of music and similar entertainment products. Design/methodology/approach – In-depth interviews using experts within the music field were used to penetrate the private worlds of musical theatre enthusiasts. Multiple qualitative analytic techniques were used to explore the different aspects of the self underlying music consumption. Findings – Repeated exposure to musical theatre allowed subjects to refine their consumption of specific performances that reflect the preferred aspect of their extended self. It is found higher order consumption needs are an integral part of the extended self, and form an important basis for consumption decisions. Of particular importance is the reflection of the self that assists others in their consumption choices. Originality/value – Present research widely recognises consumers are seeking more than just “entertainment” when they consume an entertainment product, but struggle to characterise what it is consumers are actually seeking. This research provides this insight through an elaboration of the extended self-model.

scholarly journals Guilin Tourism Image Perception Based on Web Text Analysis

2020 ◽  
Vol 1549 ◽  
pp. 022045
Author(s):  
Man Zhou ◽  
Huiying Jia ◽  
Zhen Yan
Keyword(s):  
Text Analysis ◽  
Image Perception ◽  
Tourism Image

Research on an Enhanced web Information Processing Technology based on AIS text Mining

2020 ◽  
Vol 13 ◽  
Author(s):  
Canhui Li
Keyword(s):  
Text Mining ◽  
Symmetric Matrix ◽  
Information Support ◽  
Web Content ◽  
Mining System ◽  
Information Efficiency ◽  
Web Content Mining ◽  
Content Mining ◽  
Web Text Mining ◽  
Text Mining System

Background:: To improve the information efficiency in web text mining, filtration is utilized. Methods:: A web content mining technology based on web text mining, augmented information support (AIS), is proposed for improving the web text mining efficiency. Additionally, the AIS technology is applied to the Xiangshan science conference website, and AIS4XSSC text mining system is developed. The developed system is tested for its efficiency, and its main functions are discussed. Results:: 192 documents are represented by 8352 vectors, and 192 × 8352 vectors are obtained; the similarity between 192 vectors is calculated using the cosine of included angle, 192 × 192 symmetric matrix is obtained, and 35 categories are formed by hierarchical clustering by using similarity between texts. Conclusion:: The results show that the AIS technology can effectively extract information from a large amount of web texts. The proposed system improves information retrieval efficiently and can push the valuable information to users.

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