scholarly journals Abstractive Review Summarization based on Improved Attention Mechanism with Pointer Generator Network Model

Webology ◽  
2021 ◽  
Vol 18 (1) ◽  
pp. 77-91
Author(s):  
J. Shobana ◽  
M. Murali
Keyword(s):  
Network Model ◽  
Online Reviews ◽  
Semantic Knowledge ◽  
Attention Mechanism ◽  
Summary Report ◽  
Source Text ◽  
Review Summarization ◽  
Evaluation Metric

Nowadays online reviews play an important role by giving an helping hand to the customers to know about other customer’s opinions about the product they are going to purchase. This also guides the organizations as well as government sectors to increase their quality of product and services. So automatic review summarization becomes more important rather than summarizing it manually as it saves time. The aim of this work is to produce a comprehensive summary which includes all key content from the source text. The Proposed Automatic Review Summarization model with improved attention mechanism increases the semantic knowledge and thus improves the summary’s eminence. This encoder-decoder model aims to generate summary in an abstractive way. The Pointer generator mechanism solves the problem of rare words which are out-of-vocabulary and the repetition issues are overcome by coverage mechanism. Experiments were conducted on Amazon’s mobile reviews dataset reveals that the proposed methodology generated more accurate abstractive review summarization when compared with existing techniques. The performance of the summary report is measured using the evaluation metric ROUGE.

scholarly journals Text summarization based on multi-head self-attention mechanism and pointer network

2021 ◽  
Author(s):  
Dong Qiu ◽  
Bing Yang
Keyword(s):  
Semantic Information ◽  
Training Model ◽  
Attention Mechanism ◽  
Text Summarization ◽  
Original Text ◽  
Grammatical Structure ◽  
Source Text ◽  
Inherent Feature ◽  
Feature Information

AbstractExisting text summarization methods mainly rely on the mapping between manually labeled standard summaries and the original text for feature extraction, often ignoring the internal structure and semantic feature information of the original document. Therefore, the text summary extracted by the existing model has the problems of grammatical structure errors and semantic deviation from the original text. This paper attempts to enhance the model’s attention to the inherent feature information of the source text so that the model can more accurately identify the grammatical structure and semantic information of the document. Therefore, this paper proposes a model based on the multi-head self-attention mechanism and the soft attention mechanism. By introducing an improved multi-head self-attention mechanism in the model coding stage, the training model enables the correct summary syntax and semantic information to obtain higher weight, thereby making the generated summary more coherent and accurate. At the same time, the pointer network model is adopted, and the coverage mechanism is improved to solve out-of-vocabulary and repetitive problems when generating abstracts. This article uses CNN/DailyMail dataset to verify the model proposed in this article and uses the ROUGE indicator to evaluate the model. The experimental results show that the model in this article improves the quality of the generated summary compared with other models.

An interpretable mechanism for personalized recommendation based on cross feature

2021 ◽  
pp. 1-12
Author(s):  
Lv YE ◽  
Yue Yang ◽  
Jian-Xu Zeng
Keyword(s):  
Recommender System ◽  
Online Shopping ◽  
Side Information ◽  
Attention Mechanism ◽  
Personalized Recommendation ◽  
Model Based ◽  
Embedded Model ◽  
Feature Attention ◽  
Match Score

The existing recommender system provides personalized recommendation service for users in online shopping, entertainment, and other activities. In order to improve the probability of users accepting the system’s recommendation service, compared with the traditional recommender system, the interpretable recommender system will give the recommendation reasons and results at the same time. In this paper, an interpretable recommendation model based on XGBoost tree is proposed to obtain comprehensible and effective cross features from side information. The results are input into the embedded model based on attention mechanism to capture the invisible interaction among user IDs, item IDs and cross features. The captured interactions are used to predict the match score between the user and the recommended item. Cross-feature attention score is used to generate different recommendation reasons for different user-items.Experimental results show that the proposed algorithm can guarantee the quality of recommendation. The transparency and readability of the recommendation process has been improved by providing reference reasons. This method can help users better understand the recommendation behavior of the system and has certain enlightenment to help the recommender system become more personalized and intelligent.

Customer Online Feedback with an Identity Versus No Identity: The Influence on Review Comments

2021 ◽  
pp. 109634802098888
Author(s):  
Dan Jin ◽  
Robin B. DiPietro ◽  
Nicholas M. Watanabe
Keyword(s):  
Online Community ◽  
Online Reviews ◽  
Purchasing Behavior ◽  
Mediation Effects ◽  
Driven Systems ◽  
Customer Reviews ◽  
Significant Difference ◽  
Online Feedback ◽  
The Relationship

As customers’ consumption is increasingly dominated by technology-driven systems, online self-verification becomes an important aspect of customers’ online purchasing behavior and plays a significant role in shaping social interactions in the online community. Across two studies, we examine whether online self-verification with an identity versus without an identity will lead to the different quality of online reviews. Study 1 used topic modeling with actual data stripped from Facebook and TripAdvisor customer online review sites and showed no difference between customer reviews underpinned with an identity or without. Likewise, Study 2 used an experimental design and found no significant difference between customer reviews with or without an identity. However, significant mediation effects of social ties and social capital were found when measuring the relationship between online self-verification and customer reviews. The findings build on the literature of user-generated online reviews and have important implications for academics and hospitality practitioners.

scholarly journals Humans rely more on algorithms than social influence as a task becomes more difficult

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eric Bogert ◽  
Aaron Schecter ◽  
Richard T. Watson
Keyword(s):  
Decision Making ◽  
Social Media ◽  
Social Influence ◽  
Correct Answer ◽  
Online Reviews ◽  
Personal Networks ◽  
Human Judgment ◽  
Individual Decision ◽  
Individual Decision Making

AbstractAlgorithms have begun to encroach on tasks traditionally reserved for human judgment and are increasingly capable of performing well in novel, difficult tasks. At the same time, social influence, through social media, online reviews, or personal networks, is one of the most potent forces affecting individual decision-making. In three preregistered online experiments, we found that people rely more on algorithmic advice relative to social influence as tasks become more difficult. All three experiments focused on an intellective task with a correct answer and found that subjects relied more on algorithmic advice as difficulty increased. This effect persisted even after controlling for the quality of the advice, the numeracy and accuracy of the subjects, and whether subjects were exposed to only one source of advice, or both sources. Subjects also tended to more strongly disregard inaccurate advice labeled as algorithmic compared to equally inaccurate advice labeled as coming from a crowd of peers.

scholarly journals Assessing the quality of ionospheric models through GNSS positioning error: methodology and results

GPS Solutions ◽  
2019 ◽  
Vol 24 (1) ◽  
Author(s):  
Adrià Rovira-Garcia ◽  
Deimos Ibáñez-Segura ◽  
Raul Orús-Perez ◽  
José Miguel Juan ◽  
Jaume Sanz ◽  
...  
Keyword(s):  
Satellite System ◽  
Ionospheric Delay ◽  
Single Frequency ◽  
Positioning Error ◽  
Dual Frequency ◽  
Error Sources ◽  
Ionospheric Models ◽  
Evaluation Metric ◽  
Global Navigation Satellite

Abstract Single-frequency users of the global navigation satellite system (GNSS) must correct for the ionospheric delay. These corrections are available from global ionospheric models (GIMs). Therefore, the accuracy of the GIM is important because the unmodeled or incorrectly part of ionospheric delay contributes to the positioning error of GNSS-based positioning. However, the positioning error of receivers located at known coordinates can be used to infer the accuracy of GIMs in a simple manner. This is why assessment of GIMs by means of the position domain is often used as an alternative to assessments in the ionospheric delay domain. The latter method requires accurate reference ionospheric values obtained from a network solution and complex geodetic modeling. However, evaluations using the positioning error method present several difficulties, as evidenced in recent works, that can lead to inconsistent results compared to the tests using the ionospheric delay domain. We analyze the reasons why such inconsistencies occur, applying both methodologies. We have computed the position of 34 permanent stations for the entire year of 2014 within the last Solar Maximum. The positioning tests have been done using code pseudoranges and carrier-phase leveled (CCL) measurements. We identify the error sources that make it difficult to distinguish the part of the positioning error that is attributable to the ionospheric correction: the measurement noise, pseudorange multipath, evaluation metric, and outliers. Once these error sources are considered, we obtain equivalent results to those found in the ionospheric delay domain assessments. Accurate GIMs can provide single-frequency navigation positioning at the decimeter level using CCL measurements and better positions than those obtained using the dual-frequency ionospheric-free combination of pseudoranges. Finally, some recommendations are provided for further studies of ionospheric models using the position domain method.

scholarly journals Research on the Influence of E-commerce service quality of fresh Agricultural products on customer satisfaction

2020 ◽  
Vol 189 ◽  
pp. 01022
Author(s):  
Xu xin ◽  
Chen jiaying
Keyword(s):  
Customer Satisfaction ◽  
Service Quality ◽  
Significant Influence ◽  
Online Reviews ◽  
Service Level ◽  
Competitive Advantages ◽  
Web Crawler ◽  
Evaluation Indexes ◽  
Healthy Development

Analyzing the influence of service quality on customer satisfaction can help fresh e-commerce enterprises to better understand their own service level, formulate better service strategies and improve their competitive advantages, so as to promote the sustainable and healthy development of fresh e-commerce industry. In this paper, first of all, with the aid of web crawler, acquisition of jingdong mall fresh category contains fruit, vegetables, meat and seafood aquaculture 4 products on the number of online comments and evaluation star, and word frequency statistics and extract the data collected from online reviews of consumers to pay attention to the quality of service measures, after using qualitative analysis software - NVivo coding and grade, finally, the variable of descriptive statistics, correlation analysis and regression analysis. The results show that the tangibility, reliability, empathy and responsiveness of service quality have significant influence on customer satisfaction, and other evaluation indexes of guarantee quality have significant influence on customer satisfaction except delivery.

scholarly journals Impact of Translation Techniques and Ideology Quality Text Translation in Mantra Jamuan Laut

2020 ◽  
Vol 3 (2) ◽  
pp. 1518-1529
Author(s):  
Dewi Kesuma Nasution
Keyword(s):  
Source Text ◽  
Source Language ◽  
Translation Technique ◽  
Translation Techniques ◽  
North Sumatra ◽  
Descriptive Qualitative

Mantra Jamuan Laut is spells or words used by a sea-handler in the process of Ritual Ceremony among Malay society in Kabupaten Serdang Bedagai, North Sumatra - Indonesia. This study deals with translation technique, ideologies and quality of the translated text of sea repast incantation from Malay language into English. There was 82 clauses of translated text as the data. The source of data is the utterances of a sea-handler and FGD. Descriptive qualitative was applied by using Molina and Albir’s theory to find out the translation techniques meanwhile the theory of Nababan & Machali used to figure out the quality of the translation. Considering the fact that the data which consists of four incantations are translated by five translators, then the results of their translation vary. From the analysis, it was found that there were 11 techniques of 18 applied with literal as the most dominant technique. Thereby the translators embraced foreignization ideology that mainly focuses on the source text. The utilization of foreignization ideology and the use of source language-oriented translation techniques showed that intercultural and thematic knowledge of the translators are insufficient. Since the frequency of literal technique was less than 25%, the quality of translated-text was regarded as ‘fair’.

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