Analysis of Personal Preferences Influencing on Buyer's Behavior under the B2C and C2C Mode

Yang, Yi; Liu, Wenwen; Zhu, Wenjun

doi:10.1109/bife.2011.17

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…Next, based on Experimental Group 1, Experimental Group 2 is designed to allow students to conduct card sorting themselves, which can accurately discover the mental models of the student users [20].…”

Section: Framework Processmentioning

confidence: 99%

Research on information construction of university management system app based on cognitive model

Shi-Shi,

Qin-Ling

2023

ACE

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Based on the results of interviews conducted with university students in a certain university in Yunnan Province, this study identifies the problems of excessive information navigation, complex interface layout, and difficulty in locating the school system within the university management system APP. From the perspective of information architecture, this study designs a cognitive model that is suitable for the university management system APP of a certain university in Yunnan Province. By conducting tracking surveys and interviews with students from different majors, the study utilizes the affinity diagram method to construct a cognitive model for student users, which is further categorized by involving 10 participants. The data obtained after categorization is analyzed using hierarchical cluster analysis, and the information construction of the university management system APP is restructured accordingly. Through experiments, the characteristics and existing problems of the informationization construction of the university management system APP are determined, and the navigation label information of the management system is improved. The cognitive model of the university management system APP is reconstructed, resulting in the development of navigation names and classification methods for information construction that align with the cognitive models of student users. The research findings provide a basis and reference for other university management system APPs.

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Section: Framework Processmentioning

confidence: 99%

Research on information construction of university management system app based on cognitive model

Shi-Shi,

Qin-Ling

2023

ACE

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“…A lightweighted blockchain BERT model is used to correctly extract personnel attribute entities, and the trained BERT model is used to classify event instance vectors, construct a hierarchical personnel information template, and solve the problem of personnel attribute association. e BERT [10] pretrained language model achieves the best results on 11 natural language processing tasks, and applying BERT to the named entity recognition task can achieve better results. Entity relation extraction refers to extracting predefined entity relations from unstructured text based on entity recognition.…”

Section: Introductionmentioning

confidence: 99%

Identification of End-User Economical Relationship Graph Using Lightweight Blockchain-Based BERT Model

Jagdish¹,

Shah²,

Agarwal

et al. 2022

Computational Intelligence and Neuroscience

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Current methods for extracting information from user resumes do not work well with unstructured user resumes in economic announcements, and they do not work well with documents that have the same users in them. Unstructured user information is turned into structured user information templates in this study. It also proposes a way to build person relationship graphs in the field of economics. First, the lightweight blockchain-based BERT model (B-BERT) is trained. The learned B-BERT pretraining model is then utilized to get the event instance vector, categorize it appropriately, and populate the hierarchical user information templates with accurate user characteristics. The aim of this research is that it has investigated the approach of creating character connection graphs in the Chinese financial system and suggests a framework for doing so in the economic sector. Furthermore, the relationship between users is found through the filled-in user information template, and a graph of user relationships is made. This is how it works: finally, the experiment is checked by filling in a manually annotated dataset. In tests, the method can be used to get text information from unstructured economic user resumes and build a relationship map of people in the financial field. The experimental results show that the proposed approach is capable of efficiently retrieving information from unstructured financial personnel resume text and generating a character relationship graph in the economic sphere.

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Exploring the Effects of Pet Preference, Presence, and Personality on Depression Symptoms

Puskey

Coy

2020

Anthrozoös

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Analysis of Personal Preferences Influencing on Buyer's Behavior under the B2C and C2C Mode

Cited by 3 publications

References 6 publications

Research on information construction of university management system app based on cognitive model

Research on information construction of university management system app based on cognitive model

Identification of End-User Economical Relationship Graph Using Lightweight Blockchain-Based BERT Model

Exploring the Effects of Pet Preference, Presence, and Personality on Depression Symptoms

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