XGBRS Framework Integrated with Word2Vec Sentiment Analysis for Augmented Drug Recommendation

Paliwal, Shweta; Mishra, Amit Kumar; Mishra, Ram Krishn; Nawaz, Nishad; Senthilkumar, M.

doi:10.32604/cmc.2022.025858

Cited by 17 publications

(9 citation statements)

References 31 publications

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“…Paliwal et al [15] designed a recommendation system based on the fusion of sentiment analysis and gradient boosting. The user reviews are used for finding the polarity of the sentiments, which is then used as input for gradient boost to generate the drug recommendation.…”

Section: Related Workmentioning

confidence: 99%

Improving Recommendation for Effective Personalization in Context-Aware Data Using Novel Neural Network

Sujatha¹,

Abirami²

2023

Computer Systems Science and Engineering

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The digital technologies that run based on users' content provide a platform for users to help air their opinions on various aspects of a particular subject or product. The recommendation agents play a crucial role in personalizing the needs of individual users. Therefore, it is essential to improve the user experience. The recommender system focuses on recommending a set of items to a user to help the decision-making process and is prevalent across e-commerce and media websites. In Context-Aware Recommender Systems (CARS), several influential and contextual variables are identified to provide an effective recommendation. A substantial trade-off is applied in context to achieve the proper accuracy and coverage required for a collaborative recommendation. The CARS will generate more recommendations utilizing adapting them to a certain contextual situation of users. However, the key issue is how contextual information is used to create good and intelligent recommender systems. This paper proposes an Artificial Neural Network (ANN) to achieve contextual recommendations based on usergenerated reviews. The ability of ANNs to learn events and make decisions based on similar events makes it effective for personalized recommendations in CARS. Thus, the most appropriate contexts in which a user should choose an item or service are achieved. This work converts every label set into a Multi-Label Classification (MLC) problem to enhance recommendations. Experimental results show that the proposed ANN performs better in the Binary Relevance (BR) Instance-Based Classifier, the BR Decision Tree, and the Multi-label SVM for Trip Advisor and LDOS-CoMoDa Dataset. Furthermore, the accuracy of the proposed ANN achieves better results by 1.1% to 6.1% compared to other existing methods.

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Section: Related Workmentioning

confidence: 99%

Improving Recommendation for Effective Personalization in Context-Aware Data Using Novel Neural Network

Sujatha¹,

Abirami²

2023

Computer Systems Science and Engineering

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“…A new basis leading to high synthetic efficiency of current interest in developing reactions In the light, carboxylic acid chlorides in water forming direct coupling with terminal alkynes Very desirable. However, carboxylic acid Halides are very water sensitive Common sense [13]. Metal-catalyzed carbocyclization of alkynes functionalized of particular note are external nucleophiles, because it is an addition to carbocyclic products Introduces the function.…”

Section: Alkynesmentioning

confidence: 99%

“…DEMATEL is its components a system or between several available alternatives A useful tool for exploring structure and relationships is proper. [13]. Establishing a rating structure model, combined factor For analysis and determination of the weight of the criterion DEMATEL method is also introduced.…”

Section: Dematelmentioning

confidence: 99%

The Development of Terminal Alkynes in Water Using DEMATEL Method

Mamatha

Chinnasamy²,

Murugan³

2022

jmc

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In organic chemistry, an alkyne is an unsaturated; Hydrocarbon is at least one carbon-three carbon has a bond. All three alkynes are unsaturated have a bond containing hydrocarbons, Alkynes have the general formula CnH2n-2 and three the bond is called 'acetylenic bond'. is called The functional group in the alkyne is a Carbon-carbon is three binding. Aromatics are π bonds odd number of electron in the system Planar with pairs, fully coupled and are cyclic structures. In which test to conclude from analysis and Evaluation Laboratory (DEMATEL) of complex system components a cause-and-effect chain is considered correct One of the best to identify. It values relationships Interdependence between factors and identification through visual structural modeling Important to see. Alternative: Propene (C3H6), Butene (C4H8), Pentene (C5H10), Hexene (C6H12), Heptene (C7H14). Evaluation Preference: Propene (C3H6), Butene (C4H8), Pentene (C5H10), Hexene (C6H12), Heptene (C7H14). The result it is seen that Hexene (C6H12) is got the first rank where as is the Pentene (C5H10) is having the lowest rank. The value of the dataset for Alkynes in Test and evaluate decision making the lab shows that it results in Hexene (C6H12) and top ranking.

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“…Word2vec [34], shown in Figure 3, is used in order to convert the tweets into the vector format. Statistical computations on such word vectors allow us to discover connections between the terms.…”

Section: Tweet Vectorizationmentioning

confidence: 99%

Cluster-Based Knowledge Graph and Entity-Relation Representation on Tourism Economical Sentiments

et al. 2022

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The tourism industry has experienced fast and sustainable growth over the years in the economic sector. The data available online on the ever-growing tourism sector must be given importance as it provides crucial economic insights, which can be helpful for consumers and governments. Natural language processing (NLP) techniques have traditionally been used to tackle the issues of structuring of unprocessed data, and the representation of the data in a knowledge-based system. NLP is able to capture the full richness of the text by extracting the entity and relationship from the processed data, which is gathered from various social media platforms, webpages, blogs, and other online sources, while successfully taking into consideration the semantics of the text. With the purpose of detecting connections between tourism and economy, the research aims to present a visual representation of the refined data using knowledge graphs. In this research, the data has been gathered from Twitter using keyword extraction techniques with an emphasis on tourism and economy. The research uses TextBlob to convert the tweets to numeric vector representations and further uses clustering techniques to group similar entities. A cluster-wise knowledge graph has been constructed, which comprises a large number of relationships among various factors, that visualize entities and their relationships connecting tourism and economy.

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XGBRS Framework Integrated with Word2Vec Sentiment Analysis for Augmented Drug Recommendation

Cited by 17 publications

References 31 publications

Improving Recommendation for Effective Personalization in Context-Aware Data Using Novel Neural Network

Improving Recommendation for Effective Personalization in Context-Aware Data Using Novel Neural Network

The Development of Terminal Alkynes in Water Using DEMATEL Method

Cluster-Based Knowledge Graph and Entity-Relation Representation on Tourism Economical Sentiments

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