Pub Date : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544825
Zhong-hai Wu
Efficient data flow optimization for the Internet middleware on application to the ideological online interactive system is studied in this manuscript. Our application research is mainly to discover the calling relationship and calling methods between the application and the database, to then clarify the compatibility characteristics of the application modules and the database calling middleware, and to clarify the transformation points of the application in the conversion of each module. The superword-level parallel vectorization is used at a finer granularity, and then it will be applied for the data flow analysis. The designed model is then applied to the online interactive system. The proposed model can effectively improve the online class efficiency and the feedback information is positive.
{"title":"Efficient Data Flow Optimization for Internet Middleware on Application to Ideological Online Interactive System","authors":"Zhong-hai Wu","doi":"10.1109/ICIRCA51532.2021.9544825","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544825","url":null,"abstract":"Efficient data flow optimization for the Internet middleware on application to the ideological online interactive system is studied in this manuscript. Our application research is mainly to discover the calling relationship and calling methods between the application and the database, to then clarify the compatibility characteristics of the application modules and the database calling middleware, and to clarify the transformation points of the application in the conversion of each module. The superword-level parallel vectorization is used at a finer granularity, and then it will be applied for the data flow analysis. The designed model is then applied to the online interactive system. The proposed model can effectively improve the online class efficiency and the feedback information is positive.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122451698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9545008
S. K. Narayanan, S. Dhanasekaran, V. Vasudevan
Cyber-Physical Systems (CPS) usually include a mix of movable things, embedded computers, and systems to keep track as well as actuate together with the encompassing real life. These computing components are generally wireless, interconnected to talk about interaction and data with one another, with the server component, and with cloud computing expertise. When it comes to such a heterogeneous atmosphere, brand new uses develop in order to meet ever-increasing requirements as well as these're a crucial problem on the processing features of products. For instance, instant traveling methods, producing locations, wise community managing, and so on. In order to fulfill the demands of stated application program contexts, the device is able to make computing procedures to disperse the work above the system and also a cloud computing server. Several choices develop within relation to what network nodes must support the delivery of all of the procedures. This particular paper concentrates on this issue by introducing a sent-out computational design and dynamically discuss the activities among the computing nodes as well as thinking about the natural variability on the context inside the locations. The approach of ours encourages the integration of the computing online resources, with externally provided cloud expertise, to satisfy contemporary program demands. The outcome of the Proposed design satisfies the shared computation level with energy efficient schemes and aslo achieved the response level in good level.
{"title":"A shared computational model using distributed processing in a CPS enabled environment","authors":"S. K. Narayanan, S. Dhanasekaran, V. Vasudevan","doi":"10.1109/ICIRCA51532.2021.9545008","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9545008","url":null,"abstract":"Cyber-Physical Systems (CPS) usually include a mix of movable things, embedded computers, and systems to keep track as well as actuate together with the encompassing real life. These computing components are generally wireless, interconnected to talk about interaction and data with one another, with the server component, and with cloud computing expertise. When it comes to such a heterogeneous atmosphere, brand new uses develop in order to meet ever-increasing requirements as well as these're a crucial problem on the processing features of products. For instance, instant traveling methods, producing locations, wise community managing, and so on. In order to fulfill the demands of stated application program contexts, the device is able to make computing procedures to disperse the work above the system and also a cloud computing server. Several choices develop within relation to what network nodes must support the delivery of all of the procedures. This particular paper concentrates on this issue by introducing a sent-out computational design and dynamically discuss the activities among the computing nodes as well as thinking about the natural variability on the context inside the locations. The approach of ours encourages the integration of the computing online resources, with externally provided cloud expertise, to satisfy contemporary program demands. The outcome of the Proposed design satisfies the shared computation level with energy efficient schemes and aslo achieved the response level in good level.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"261 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122690395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544533
Shao-long Jiang
Enterprise taxation smart monitoring system based on intelligent background data extraction is designed in the proposed study. At present, the commonly used core volume rendering technology can display high-quality three-dimensional object detail information, with this theoretical basis; this research work design and also implement the novel data segmentation pipeline. The system is implemented with the platform construction and the smart monitoring model is combined. Also, the designed system can effectively collect and process data.
{"title":"Enterprise Taxation Smart Monitoring System Based on Intelligent Background Data Extraction","authors":"Shao-long Jiang","doi":"10.1109/ICIRCA51532.2021.9544533","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544533","url":null,"abstract":"Enterprise taxation smart monitoring system based on intelligent background data extraction is designed in the proposed study. At present, the commonly used core volume rendering technology can display high-quality three-dimensional object detail information, with this theoretical basis; this research work design and also implement the novel data segmentation pipeline. The system is implemented with the platform construction and the smart monitoring model is combined. Also, the designed system can effectively collect and process data.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122888532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544524
Gourab Dhabal, Jaykumar S. Lachure, R. Doriya
Agriculture is the backbone of the developing countries and plays a primary role in the economy in these countries. For bringing in the most productivity, the decision of planting a suitable crop in a particular location is necessary. But, there is a general problem among farmers and other agricultural activists that they don't opt for better scientifically proven methods for crop recommendation. Thus, our proposed work would help farmers in selecting the right crop based on factors like cost of cultivation, cost of production, yield to increase productivity and get more profit out of this proposed technique. This paper discusses about the different machine learning algorithms to know about them, their metrics evaluation for a certain dataset, and finally, a proposed methodology that performs better than other learners. The paper proposes a methodology in which decision tree, kth nearest neighbor, logistic regression, random forest and gradient boosting classifier are used to process the data set and then, these learners are passed through an ensemble model called voting classifier to get a more improved outcome. The comparison between these algorithms is also shown in terms of metrics – accuracy, f1 score and execution time on the certain dataset used. This paper also discusses cloud computing and the cloud server processing machine learning algorithms to give required output enquired by the end user.
{"title":"Crop Recommendation System with Cloud Computing","authors":"Gourab Dhabal, Jaykumar S. Lachure, R. Doriya","doi":"10.1109/ICIRCA51532.2021.9544524","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544524","url":null,"abstract":"Agriculture is the backbone of the developing countries and plays a primary role in the economy in these countries. For bringing in the most productivity, the decision of planting a suitable crop in a particular location is necessary. But, there is a general problem among farmers and other agricultural activists that they don't opt for better scientifically proven methods for crop recommendation. Thus, our proposed work would help farmers in selecting the right crop based on factors like cost of cultivation, cost of production, yield to increase productivity and get more profit out of this proposed technique. This paper discusses about the different machine learning algorithms to know about them, their metrics evaluation for a certain dataset, and finally, a proposed methodology that performs better than other learners. The paper proposes a methodology in which decision tree, kth nearest neighbor, logistic regression, random forest and gradient boosting classifier are used to process the data set and then, these learners are passed through an ensemble model called voting classifier to get a more improved outcome. The comparison between these algorithms is also shown in terms of metrics – accuracy, f1 score and execution time on the certain dataset used. This paper also discusses cloud computing and the cloud server processing machine learning algorithms to give required output enquired by the end user.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128040474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544896
J. R. Annam, Pavan Kumar Ande, Bhargavi Kanuri, C. Prasad, B. S. Babu, Poojitha Tatineni
This research paper suggests to build on the results obtained by Goldin and Reck (2020). It suggests to collect a dataset that can be used to test their method. At the same time, the results from the analysis of this dataset will produce framing-consistent estimates of users' privacy setting preferences. The test of Goldin and Reck (2020)'s method will constitute a methodological contribution to the literature on revealed preferences under framing. The preference estimates will contribute to the literature on privacy preferences and will have implications for policy makers concerned with the security concern on personal data present on the internet. It is proposed to write a similar browser add-on to track people's decision about browser cookie settings. According to the General Data Protection Regulation (GDPR) users, who visit a website from within the European Union or the European Economic Area must be asked for their stated consent on storing browser cookies (General Data Protection Regulation 2020). For the intents of this research proposal, one can divide browser cookies into two groups. First, there are essential cookies that are necessary to guarantee the website's functionality. Second, there are third-party ad-tracking cookies. A website's host still has a monetary incentive to nudge users to allow for the ad-tracking cookies. This can be done by choosing the default cookie settings.
{"title":"User valuation of secrecy Framing based on General Data Protection Regulation (GDPR) users","authors":"J. R. Annam, Pavan Kumar Ande, Bhargavi Kanuri, C. Prasad, B. S. Babu, Poojitha Tatineni","doi":"10.1109/ICIRCA51532.2021.9544896","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544896","url":null,"abstract":"This research paper suggests to build on the results obtained by Goldin and Reck (2020). It suggests to collect a dataset that can be used to test their method. At the same time, the results from the analysis of this dataset will produce framing-consistent estimates of users' privacy setting preferences. The test of Goldin and Reck (2020)'s method will constitute a methodological contribution to the literature on revealed preferences under framing. The preference estimates will contribute to the literature on privacy preferences and will have implications for policy makers concerned with the security concern on personal data present on the internet. It is proposed to write a similar browser add-on to track people's decision about browser cookie settings. According to the General Data Protection Regulation (GDPR) users, who visit a website from within the European Union or the European Economic Area must be asked for their stated consent on storing browser cookies (General Data Protection Regulation 2020). For the intents of this research proposal, one can divide browser cookies into two groups. First, there are essential cookies that are necessary to guarantee the website's functionality. Second, there are third-party ad-tracking cookies. A website's host still has a monetary incentive to nudge users to allow for the ad-tracking cookies. This can be done by choosing the default cookie settings.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128072484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544985
S. Sindhura, S. Praveen, M. Safali, NidamanuruSrinivasa Rao
Buyers to whom a product would be introduced should check it to make better choices about the item. To arrive at a specific finding, various viewpoint mining methods have been suggested. Several recent developments in machine learning, especially deep learning, have led to considerable progress in solving sentiment classification problems. To achieve valuable scores as poor supervision indicators, this research work suggests an innovative deep learning system for performing product review based emotion classification. To achieve a high-level representation, one needs to learn the embedding before applying a classification layer on top of the embedding.
{"title":"Sentiment Analysis for Product Reviews Based on Weakly-Supervised Deep Embedding","authors":"S. Sindhura, S. Praveen, M. Safali, NidamanuruSrinivasa Rao","doi":"10.1109/ICIRCA51532.2021.9544985","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544985","url":null,"abstract":"Buyers to whom a product would be introduced should check it to make better choices about the item. To arrive at a specific finding, various viewpoint mining methods have been suggested. Several recent developments in machine learning, especially deep learning, have led to considerable progress in solving sentiment classification problems. To achieve valuable scores as poor supervision indicators, this research work suggests an innovative deep learning system for performing product review based emotion classification. To achieve a high-level representation, one needs to learn the embedding before applying a classification layer on top of the embedding.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128130068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544820
Aastha Arora, Ankit Vijayvargiya, Rajesh Kumar, M. Tiwari
The occurrence of work-related injury risks is extremely high in the garment industry but often ignored. These disorders not only damage the physical health of the workers but also proves to be a prominent factor while talking about loss in work time; ultimately leading to low productivity and efficiency. This paper presents a systematic approach to predict the automated diagnosis of musculoskeletal disorder among the sewing machine operators of the garment industry. The working videos of 20 participants- 10 healthy (normal) and 10 unhealthy (abnormal) were recorded from both sides- left and right. For posture evaluation, OpenPose algorithm is applied to estimate 2D human pose and to extract the joint angles of neck, trunk, upper arm and lower arm of both left and right sides, using the python math library. The extracted angles were then normalised between the range 0 (zero) to 1 (one) to prepare a classification model using the KNN Classifier. Stratified k-fold cross-validation was implemented using 10 folds which gave the accuracy of 91.3% in diagnosing the musculoskeletal disorder among the sewing machine operators.
{"title":"Machine Learning based Risk Classification of Musculoskeletal Disorder among the Garment Industry Operators","authors":"Aastha Arora, Ankit Vijayvargiya, Rajesh Kumar, M. Tiwari","doi":"10.1109/ICIRCA51532.2021.9544820","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544820","url":null,"abstract":"The occurrence of work-related injury risks is extremely high in the garment industry but often ignored. These disorders not only damage the physical health of the workers but also proves to be a prominent factor while talking about loss in work time; ultimately leading to low productivity and efficiency. This paper presents a systematic approach to predict the automated diagnosis of musculoskeletal disorder among the sewing machine operators of the garment industry. The working videos of 20 participants- 10 healthy (normal) and 10 unhealthy (abnormal) were recorded from both sides- left and right. For posture evaluation, OpenPose algorithm is applied to estimate 2D human pose and to extract the joint angles of neck, trunk, upper arm and lower arm of both left and right sides, using the python math library. The extracted angles were then normalised between the range 0 (zero) to 1 (one) to prepare a classification model using the KNN Classifier. Stratified k-fold cross-validation was implemented using 10 folds which gave the accuracy of 91.3% in diagnosing the musculoskeletal disorder among the sewing machine operators.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132555418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544837
Sajjan Kiran, Umesh Patil, P. S. Shankar, P. Ghuli
Video Subtitles are not only an essential tool for the hearing impaired, but also enhance the user's viewing experience, as they allow users to better understand and interpret different accents, even if they are of the same familiar language. Automatic Speech Recognition Systems would also eradicate the strenuous mechanical process involved in creating subtitle files for movie videos. Searching and indexing of different scenes in a video is still far behind when compared to that available for other forms like text data. With the help of Video Captioning models, the accessibility and indexing requirements of video files can be significantly improved by allowing the users to search for a particular scene/event in a video. This paper discusses about the solution offered to these requirements with the help of sequence-to-sequence recurrent neural networks. The paper also includes the different techniques involved in preprocessing the audio data and extracting features from them, the network architectures, CTC algorithm for backpropagation of error through time, suitable evaluation metrics for Sequence-to-Sequence models and the challenges involved during the designing and training phase of such models.
{"title":"Subtitle Generation and Video Scene Indexing using Recurrent Neural Networks","authors":"Sajjan Kiran, Umesh Patil, P. S. Shankar, P. Ghuli","doi":"10.1109/ICIRCA51532.2021.9544837","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544837","url":null,"abstract":"Video Subtitles are not only an essential tool for the hearing impaired, but also enhance the user's viewing experience, as they allow users to better understand and interpret different accents, even if they are of the same familiar language. Automatic Speech Recognition Systems would also eradicate the strenuous mechanical process involved in creating subtitle files for movie videos. Searching and indexing of different scenes in a video is still far behind when compared to that available for other forms like text data. With the help of Video Captioning models, the accessibility and indexing requirements of video files can be significantly improved by allowing the users to search for a particular scene/event in a video. This paper discusses about the solution offered to these requirements with the help of sequence-to-sequence recurrent neural networks. The paper also includes the different techniques involved in preprocessing the audio data and extracting features from them, the network architectures, CTC algorithm for backpropagation of error through time, suitable evaluation metrics for Sequence-to-Sequence models and the challenges involved during the designing and training phase of such models.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133276403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544666
Yunqing Li
This article aims to improve the performance of embedded video forensics and storage systems, and on the basis of introducing the status quo of digital video acquisition and video compression, it studies the realization principles of video signal acquisition, forensics, storage systems, and video playback. This design has completed the SPCE3200 processor and its development platform for research and analysis, and designed a new video forensic storage framework. This design has a certain degree of innovation and has certain practical value in the field of video capture and processing.
{"title":"Design of Video Forensics and Storage Framework Based on Embedded Technology","authors":"Yunqing Li","doi":"10.1109/ICIRCA51532.2021.9544666","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544666","url":null,"abstract":"This article aims to improve the performance of embedded video forensics and storage systems, and on the basis of introducing the status quo of digital video acquisition and video compression, it studies the realization principles of video signal acquisition, forensics, storage systems, and video playback. This design has completed the SPCE3200 processor and its development platform for research and analysis, and designed a new video forensic storage framework. This design has a certain degree of innovation and has certain practical value in the field of video capture and processing.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"545 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134282445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-02DOI: 10.1109/ICIRCA51532.2021.9544981
Sangeeth Sajan Baby, Singadi Likhit Reddy
Product Recommendation plays a major role in the revenue of an E-commerce application. But the chance of the wrong recommendation is very high and the cost of such recommendations are also very high. Why a birthday cap is always required along with the Christmas cake? - This is a kind of question that has to be considered while using the Apriori algorithm for product recommendation purpose. There might be a chance to recommend unrelated items. This paper proposes a system, which uses an improved apriori algorithm for a product recommendation, which takes the context of purchase into account.
{"title":"End to End Product Recommendation system with improvements in Apriori Algorithm","authors":"Sangeeth Sajan Baby, Singadi Likhit Reddy","doi":"10.1109/ICIRCA51532.2021.9544981","DOIUrl":"https://doi.org/10.1109/ICIRCA51532.2021.9544981","url":null,"abstract":"Product Recommendation plays a major role in the revenue of an E-commerce application. But the chance of the wrong recommendation is very high and the cost of such recommendations are also very high. Why a birthday cap is always required along with the Christmas cake? - This is a kind of question that has to be considered while using the Apriori algorithm for product recommendation purpose. There might be a chance to recommend unrelated items. This paper proposes a system, which uses an improved apriori algorithm for a product recommendation, which takes the context of purchase into account.","PeriodicalId":245244,"journal":{"name":"2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130367401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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