This document proposes a web application called Upserve to improve restaurant management and sales analysis. It aims to provide customers with a dynamic menu, recommendation system, and allow restaurants to easily analyze sales data. The system would track sales, inventory, customer information and preferences. This would help restaurants optimize their menu, create marketing campaigns, and improve the customer experience. The goals are to provide an easy to use menu, show real-time availability, highlight sales trends, and give personalized recommendations to customers. It reviews similar existing systems and algorithms that could be used to analyze data, classify customers, compare items, and make recommendations. The proposed system aims to boost restaurant sales and growth through improved technology solutions.
Different Location based Approaches in Recommendation SystemsIRJET Journal
This document discusses different location-based approaches used in recommendation systems. It begins by introducing how location characteristics play an important role in recommendation systems by providing contextual information about users and items. It then describes several examples of recommendation systems that incorporate location, such as restaurant, movie, outdoor, and shop recommendations. Next, it covers techniques commonly used to generate recommendations, such as content-based filtering, collaborative filtering, hybrid filtering, and matrix factorization. Finally, it concludes that location data is useful for generating more accurate recommendations by linking the physical and digital worlds and providing insights into user preferences and activities.
IRJET- Restaurant Table Reservation using Graphical RepresentationIRJET Journal
This document presents a proposed system for restaurant table reservation using graphical representation. The current reservation systems rely on phone calls or online reservations but lack key functionality. The proposed system aims to address issues like long wait times, inability to select preferred tables, and inefficient restaurant ratings/reviews analysis. It involves a graphical layout of the restaurant for customers to select their preferred table. It also uses algorithms to reduce wait times and natural language processing to provide an overall rating by analyzing reviews. The system is intended to improve the customer experience and increase revenues for restaurants.
This document describes a student project to develop a customer feedback system for restaurants. It discusses collecting customer feedback to improve customer satisfaction and business success. The proposed system would expand an existing feedback collection process. It would investigate factors influencing customer satisfaction and design a questionnaire to measure current satisfaction levels. The goal is to accurately interpret customer data and provide recommendations to help the business. The system would be a mobile app allowing multi-location, multi-lingual feedback collection with notification alerts and comparative reports. It aims to represent feedback visually to help owners better understand customer opinions.
Google is one of the world's most successful and popular search engines. The company has mastered the art of data analytics, using this technique to improve its products and services. The data analytics team at Google works tirelessly to gather and analyze data from various sources. The data is collected from sources like search engine logs, web analytics, social media, and more.
Once the data is collected, it is analyzed to provide insights into user behavior and preferences. Google uses this information to improve its search algorithms, understand user intent, and create personalized search results. Data analytics also helps Google to identify and resolve technical issues that could impact the user experience.
In addition to improving search results, data analytics also helps Google to improve its advertising platform. The company uses data analytics to optimize ad placement, targeting, and bidding. By analyzing user behavior, Google can serve more relevant ads to users, which leads to higher conversion rates for advertisers.
Overall, Google's use of data analytics is an integral part of its success. The company's ability to gather and analyze data allows it to continuously improve its products and services, making it the go-to search engine for millions of users worldwide.
A Survey on Customer Analytics Techniques for the Retail IndustryIRJET Journal
This document summarizes several techniques for customer analytics in the retail industry that are discussed in existing literature, including customer churn prediction, customer segmentation, and market basket analysis. It provides an overview of common algorithms used for each technique, such as classification algorithms for churn prediction, clustering algorithms for segmentation, and association rule mining for market basket analysis. It then reviews seven research papers that evaluate these techniques on retail transaction and customer data, comparing the performance of algorithms like K-means clustering, decision trees, and neural networks. The papers demonstrate how these analytical approaches can provide actionable insights for retailers to improve customer retention, target marketing, and optimize product assortments.
A User Experience Audit (UX Audit) is a method for identifying problematic areas of a digital product, exposing which aspects of a website or mobile application are causing user frustration and inhibiting conversions.
Inventory Decisions Sensitive To Demand And Lead Times In The Supply ChainaNumak & Company
Due to global competition, demand is no longer fully determined in any business area. The environment today is extremely dynamic. In such a situation, an estimation error anywhere in the supply chain is felt throughout the process. For this reason, forecasting has a very important place in supply chain management.
Sales analysis using product rating in data mining techniqueseSAT Journals
Abstract
In this paper a new product rating approach for mathematically and graphically analyzing sales of same type of products from different manufactures and with most frequent combination of items is proposed. In product sales market there is no specific rating for product of same type and combination of product purchasing pattern. By this we retrieve the best combination of products with mathematically rating. By this rating and pattern we can make graphical representation of rating and combination of product of same type to compare them with other . Data mining provide more abstract knowledge to analyze business functionalities with retail product data. The purpose of product is to fulfill need of customer , based upon it there are different company makes product of same type , by analyzing it mathematically best one can be calculated thing such as customer satisfaction , product efficiency , popularity among them.
Keywords: Data Mining, Sales Report, Product rating, Threshold value.
Different Location based Approaches in Recommendation SystemsIRJET Journal
This document discusses different location-based approaches used in recommendation systems. It begins by introducing how location characteristics play an important role in recommendation systems by providing contextual information about users and items. It then describes several examples of recommendation systems that incorporate location, such as restaurant, movie, outdoor, and shop recommendations. Next, it covers techniques commonly used to generate recommendations, such as content-based filtering, collaborative filtering, hybrid filtering, and matrix factorization. Finally, it concludes that location data is useful for generating more accurate recommendations by linking the physical and digital worlds and providing insights into user preferences and activities.
IRJET- Restaurant Table Reservation using Graphical RepresentationIRJET Journal
This document presents a proposed system for restaurant table reservation using graphical representation. The current reservation systems rely on phone calls or online reservations but lack key functionality. The proposed system aims to address issues like long wait times, inability to select preferred tables, and inefficient restaurant ratings/reviews analysis. It involves a graphical layout of the restaurant for customers to select their preferred table. It also uses algorithms to reduce wait times and natural language processing to provide an overall rating by analyzing reviews. The system is intended to improve the customer experience and increase revenues for restaurants.
This document describes a student project to develop a customer feedback system for restaurants. It discusses collecting customer feedback to improve customer satisfaction and business success. The proposed system would expand an existing feedback collection process. It would investigate factors influencing customer satisfaction and design a questionnaire to measure current satisfaction levels. The goal is to accurately interpret customer data and provide recommendations to help the business. The system would be a mobile app allowing multi-location, multi-lingual feedback collection with notification alerts and comparative reports. It aims to represent feedback visually to help owners better understand customer opinions.
Google is one of the world's most successful and popular search engines. The company has mastered the art of data analytics, using this technique to improve its products and services. The data analytics team at Google works tirelessly to gather and analyze data from various sources. The data is collected from sources like search engine logs, web analytics, social media, and more.
Once the data is collected, it is analyzed to provide insights into user behavior and preferences. Google uses this information to improve its search algorithms, understand user intent, and create personalized search results. Data analytics also helps Google to identify and resolve technical issues that could impact the user experience.
In addition to improving search results, data analytics also helps Google to improve its advertising platform. The company uses data analytics to optimize ad placement, targeting, and bidding. By analyzing user behavior, Google can serve more relevant ads to users, which leads to higher conversion rates for advertisers.
Overall, Google's use of data analytics is an integral part of its success. The company's ability to gather and analyze data allows it to continuously improve its products and services, making it the go-to search engine for millions of users worldwide.
A Survey on Customer Analytics Techniques for the Retail IndustryIRJET Journal
This document summarizes several techniques for customer analytics in the retail industry that are discussed in existing literature, including customer churn prediction, customer segmentation, and market basket analysis. It provides an overview of common algorithms used for each technique, such as classification algorithms for churn prediction, clustering algorithms for segmentation, and association rule mining for market basket analysis. It then reviews seven research papers that evaluate these techniques on retail transaction and customer data, comparing the performance of algorithms like K-means clustering, decision trees, and neural networks. The papers demonstrate how these analytical approaches can provide actionable insights for retailers to improve customer retention, target marketing, and optimize product assortments.
A User Experience Audit (UX Audit) is a method for identifying problematic areas of a digital product, exposing which aspects of a website or mobile application are causing user frustration and inhibiting conversions.
Inventory Decisions Sensitive To Demand And Lead Times In The Supply ChainaNumak & Company
Due to global competition, demand is no longer fully determined in any business area. The environment today is extremely dynamic. In such a situation, an estimation error anywhere in the supply chain is felt throughout the process. For this reason, forecasting has a very important place in supply chain management.
Sales analysis using product rating in data mining techniqueseSAT Journals
Abstract
In this paper a new product rating approach for mathematically and graphically analyzing sales of same type of products from different manufactures and with most frequent combination of items is proposed. In product sales market there is no specific rating for product of same type and combination of product purchasing pattern. By this we retrieve the best combination of products with mathematically rating. By this rating and pattern we can make graphical representation of rating and combination of product of same type to compare them with other . Data mining provide more abstract knowledge to analyze business functionalities with retail product data. The purpose of product is to fulfill need of customer , based upon it there are different company makes product of same type , by analyzing it mathematically best one can be calculated thing such as customer satisfaction , product efficiency , popularity among them.
Keywords: Data Mining, Sales Report, Product rating, Threshold value.
This document discusses process improvement and ensuring customer relationships through business intelligence. It begins by defining processes and explaining why process improvement is important. It then discusses using business intelligence tools like web analytics and search engine optimization to improve processes and monitor customer interactions on websites. Specifically, it outlines how the authors analyzed various factors that impact search engine optimization and installed analytics tools on client websites. This allowed them to generate reports on user behavior, acquisition sources, and conversions. Sending these reports to clients helped them make better marketing decisions to target the right customers and improve processes. The results of implementing these improvements were increased profits and reduced costs for clients.
The Transformative Role of Data Analysis in Enhancing Customer Experience.pdfSoumodeep Nanee Kundu
In today's highly competitive business landscape, delivering an exceptional customer experience is no longer a luxury; it's a necessity. Customer expectations have risen to unprecedented levels, and companies that prioritize and enhance the customer experience gain a significant edge. One of the most potent tools for achieving this is data analysis. In this comprehensive exploration, we will delve into how data analysis can be harnessed to improve customer experience, from understanding customer needs to tailoring personalized experiences and optimizing business processes.
This document summarizes a research paper that analyzes customer behavior on an e-commerce website based on product discounts. The researchers developed a model to track customer sessions online and collect data on browsing, purchases, and other interactions. They applied different discounts to products and used statistics like standard deviation to analyze how sales and customer behavior changed based on the discounts. The key findings were that sales initially increase with higher discounts but reach a point where further discount increases reduce sales, likely due to concerns about product quality. This research aims to help e-commerce companies optimize their discounting strategies.
Web Scraping Food Reviews Data & Sentiment Analysis– A Comprehensive Guide.pdffarhanaaansari42
Unlock insights from web scraping food reviews data. Dive deep into sentiment analysis for informed decision-making.
https://www.datazivot.com/web-scraping-food-reviews-data-analysis.php
Customer Experience Testing: The Key to Digital SuccessCognizant
In the increasingly digital world, businesses must embrace and execute a well-defined customer experience testing strategy that keeps customers loyal and satisfied.
1. Marketing research is used by companies to understand customer expectations and perceptions in order to improve their services. Various research methods are used including surveys, focus groups, and complaint tracking.
2. Two important research methods are critical incident studies, which analyze satisfying and dissatisfying customer service interactions, and requirements research, which identifies customer benefits and attributes.
3. Other techniques include post-transaction surveys conducted after each customer interaction to gauge satisfaction, and service expectation meetings between companies and large business customers. Understanding customer expectations is key to delivering quality service.
This document outlines an analysis for an online restaurant reservation system. It includes objectives to provide a convenient reservation process. The scope covers allowing online reservations and providing availability updates. Stakeholders include customers, restaurants, owners, and media. Requirements include booking, payment, availability searches, and confirmation emails. Use case diagrams, data flow diagrams, and user stories model interactions like making reservations, updating statuses, and cancellation scenarios. The analysis provides a foundation for developing the reservation system.
Web Scraping Food Reviews Data & Sentiment Analysis– A Comprehensive Guide.pptxfarhanaaansari42
Unlock insights from web scraping food reviews data. Dive deep into sentiment analysis for informed decision-making.
know more>>https://www.datazivot.com/web-scraping-food-reviews-data-analysis.php
This document provides guidelines for submitting an industry project in 6 parts. Part 1 involves product analytics, Part 2 covers growth strategies, Part 3 is the product roadmap, Part 4 includes the product and sprint backlogs, Part 5 is the product requirements document, and Part 6 is the go-to-market strategy. The submission format is specified for each part, with Parts 1, 2 and 6 to be submitted in a PowerPoint file, Parts 3 and 4 in an Excel file, and Part 5 in a Word document.
User Behavior Analytics Services In India | Senselearner
Senselearner is a leading brand offering the best user behavior analytics services and solutions in India. Their innovative tools and technologies enable businesses to gain deep insights into user behavior, helping them optimize user experience and increase conversions. Senselearner's user behavior analytics services cover everything from website and app usage analytics to customer journey mapping and segmentation. With their data-driven approach, Senselearner helps businesses understand user behavior in real-time, enabling them to make informed decisions and drive growth. Their solutions are trusted by top businesses across various industries and have helped them achieve measurable success. Choose Senselearner for reliable and effective user behavior analytics services and solutions. For more information, Visit our website: https://senselearner.com/user-behavior-analytics/
Design of recommender system based on customer reviewseSAT Journals
Abstract Recommendations play a significant role in every human life. People choose their ideas based on other’s recommendations since they trust the recommendations more. For giving recommendations there emerged a system called Recommender system. Recommender systems play a important role in E-Marketing. Many companies adopt recommender systems to increase in their sales in the market. They can establish their products such that they can attract more customers by giving offers. Many ranking approaches have emerged to rank the top product recommendation to give to user. Ratings calculated can be an explicit or impliocit rating. Popular sites are Amazon.com, Netflix.com, and Movielens.com etc. These sites help the customers to find relevant product to their interest. They play as a place where customers can find all kinds of items. They do so because recommendations given by other customers have been published after they have used the product. Those customers will have experience about the product. From the customers their view of how is the product usage has been collected. This is used in recommendations. In the Proposed system, customer’s views are used for recommendations. While new customer search products, old users views are published for the particular product. On getting the customer views, one user can trust it since common people have more confidence on words-of other people. Based on product, users are given form to fill their views.On getting views, Ratings are calculated from it. These kind of recommender system give useful recommendations since we collect views of people who are familiar with the item or product. Index Terms: Recommender system, E-Commerce, collaborative filtering, Customer reviews
The document discusses sentiment analysis of customer feedback on restaurant reviews. It provides background on how sentiment analysis is used to analyze opinions expressed in online reviews and social media posts. It then describes the methodology used in the study, which involves collecting restaurant review data, preprocessing it by cleaning data and reducing attributes, and then classifying the reviews using a naive Bayes classifier to predict if sentiments expressed are positive, negative, or neutral. The goal is to design a text analysis system to automatically classify large amounts of restaurant review data using machine learning techniques.
IRJET- Physical Design of Approximate Multiplier for Area and Power EfficiencyIRJET Journal
This document summarizes research on using statistical measures and machine learning techniques to perform sentiment analysis on product reviews. The researchers collected product review data from online sources and analyzed the sentiment and opinions expressed in the text using support vector machine classifiers. They classified reviews as positive or negative and analyzed key product features that were discussed. The results demonstrated that statistical sentiment analysis can help companies better understand customer feedback and identify popular product versions or attributes. Several related works applying techniques like naive Bayes, lexicon-based methods and aspect-based sentiment analysis on reviews from domains like movies, hotels and restaurants are also summarized.
Providing Highly Accurate Service Recommendation over Big Data using Adaptive...IRJET Journal
This document proposes an adaptive recommendation system to provide accurate service recommendations over big data. It combines content-based, item-based, and knowledge-based recommendation techniques using an adaptive collaborative filtering approach. The system aims to improve scalability, accuracy, and address cold-start problems. It uses clustering to group similar services together to reduce data size and improve recommendation accuracy. The system architecture includes administrative and visitor modules to manage products and provide recommendations respectively. Service recommendations are generated by matching users to similar neighborhoods based on item preferences.
The document describes a proposed online food ordering system. Some key points:
1. The system would allow customers to easily order food from restaurants and mess services through a mobile app. Customers could browse food menus and place orders.
2. Restaurant owners and mess services would be able to update their menus and receive orders and customer feedback in real-time through the system.
3. The proposed system aims to overcome limitations of existing food ordering systems like inaccurate paper-based systems. It would provide a more convenient and efficient ordering experience for both customers and businesses.
Unlock your website's potential with a powerful UX audit in 2024! This guide explores UX audits, user experience audits, UX audit reports, and everything in between.
IRJET- Customer Buying Prediction using Machine-Learning Techniques: A SurveyIRJET Journal
1) The document discusses using machine learning techniques to predict customer purchasing and churn based on their personal and behavioral data.
2) It reviews several machine learning algorithms that have been used for prediction, including random forest, logistic regression, naive bayes, and support vector machines.
3) Deep learning techniques are also discussed, including the use of convolutional neural networks to reveal hidden patterns in customer data and predict purchases and churn.
Recommender System- Analyzing products by mining Data StreamsIRJET Journal
This document discusses several papers related to recommender systems and analyzing products and reviews. It discusses using data mining techniques like SVM, Naive Bayes and clustering algorithms to build recommendation systems for small businesses based on product sales and reviews. It also discusses detecting fake reviews using language analysis and summarizes papers on using Power BI for data visualization and analyzing research data. Key aspects covered include using data streams to provide recommendations in real-time, detecting fake reviews, using data visualization tools like Power BI for analysis, and combining clustering and association rule mining for recommendations.
Today there is a lot of buzz around customer experience. Many companies have realized that investments in customer experience improvement is important not just because it helps to boost the bottom lines of their businesses but because it takes at least 4 to 6 times more cost to acquire a new customer than to retain an existing customer.
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
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This document discusses process improvement and ensuring customer relationships through business intelligence. It begins by defining processes and explaining why process improvement is important. It then discusses using business intelligence tools like web analytics and search engine optimization to improve processes and monitor customer interactions on websites. Specifically, it outlines how the authors analyzed various factors that impact search engine optimization and installed analytics tools on client websites. This allowed them to generate reports on user behavior, acquisition sources, and conversions. Sending these reports to clients helped them make better marketing decisions to target the right customers and improve processes. The results of implementing these improvements were increased profits and reduced costs for clients.
The Transformative Role of Data Analysis in Enhancing Customer Experience.pdfSoumodeep Nanee Kundu
In today's highly competitive business landscape, delivering an exceptional customer experience is no longer a luxury; it's a necessity. Customer expectations have risen to unprecedented levels, and companies that prioritize and enhance the customer experience gain a significant edge. One of the most potent tools for achieving this is data analysis. In this comprehensive exploration, we will delve into how data analysis can be harnessed to improve customer experience, from understanding customer needs to tailoring personalized experiences and optimizing business processes.
This document summarizes a research paper that analyzes customer behavior on an e-commerce website based on product discounts. The researchers developed a model to track customer sessions online and collect data on browsing, purchases, and other interactions. They applied different discounts to products and used statistics like standard deviation to analyze how sales and customer behavior changed based on the discounts. The key findings were that sales initially increase with higher discounts but reach a point where further discount increases reduce sales, likely due to concerns about product quality. This research aims to help e-commerce companies optimize their discounting strategies.
Web Scraping Food Reviews Data & Sentiment Analysis– A Comprehensive Guide.pdffarhanaaansari42
Unlock insights from web scraping food reviews data. Dive deep into sentiment analysis for informed decision-making.
https://www.datazivot.com/web-scraping-food-reviews-data-analysis.php
Customer Experience Testing: The Key to Digital SuccessCognizant
In the increasingly digital world, businesses must embrace and execute a well-defined customer experience testing strategy that keeps customers loyal and satisfied.
1. Marketing research is used by companies to understand customer expectations and perceptions in order to improve their services. Various research methods are used including surveys, focus groups, and complaint tracking.
2. Two important research methods are critical incident studies, which analyze satisfying and dissatisfying customer service interactions, and requirements research, which identifies customer benefits and attributes.
3. Other techniques include post-transaction surveys conducted after each customer interaction to gauge satisfaction, and service expectation meetings between companies and large business customers. Understanding customer expectations is key to delivering quality service.
This document outlines an analysis for an online restaurant reservation system. It includes objectives to provide a convenient reservation process. The scope covers allowing online reservations and providing availability updates. Stakeholders include customers, restaurants, owners, and media. Requirements include booking, payment, availability searches, and confirmation emails. Use case diagrams, data flow diagrams, and user stories model interactions like making reservations, updating statuses, and cancellation scenarios. The analysis provides a foundation for developing the reservation system.
Web Scraping Food Reviews Data & Sentiment Analysis– A Comprehensive Guide.pptxfarhanaaansari42
Unlock insights from web scraping food reviews data. Dive deep into sentiment analysis for informed decision-making.
know more>>https://www.datazivot.com/web-scraping-food-reviews-data-analysis.php
This document provides guidelines for submitting an industry project in 6 parts. Part 1 involves product analytics, Part 2 covers growth strategies, Part 3 is the product roadmap, Part 4 includes the product and sprint backlogs, Part 5 is the product requirements document, and Part 6 is the go-to-market strategy. The submission format is specified for each part, with Parts 1, 2 and 6 to be submitted in a PowerPoint file, Parts 3 and 4 in an Excel file, and Part 5 in a Word document.
User Behavior Analytics Services In India | Senselearner
Senselearner is a leading brand offering the best user behavior analytics services and solutions in India. Their innovative tools and technologies enable businesses to gain deep insights into user behavior, helping them optimize user experience and increase conversions. Senselearner's user behavior analytics services cover everything from website and app usage analytics to customer journey mapping and segmentation. With their data-driven approach, Senselearner helps businesses understand user behavior in real-time, enabling them to make informed decisions and drive growth. Their solutions are trusted by top businesses across various industries and have helped them achieve measurable success. Choose Senselearner for reliable and effective user behavior analytics services and solutions. For more information, Visit our website: https://senselearner.com/user-behavior-analytics/
Design of recommender system based on customer reviewseSAT Journals
Abstract Recommendations play a significant role in every human life. People choose their ideas based on other’s recommendations since they trust the recommendations more. For giving recommendations there emerged a system called Recommender system. Recommender systems play a important role in E-Marketing. Many companies adopt recommender systems to increase in their sales in the market. They can establish their products such that they can attract more customers by giving offers. Many ranking approaches have emerged to rank the top product recommendation to give to user. Ratings calculated can be an explicit or impliocit rating. Popular sites are Amazon.com, Netflix.com, and Movielens.com etc. These sites help the customers to find relevant product to their interest. They play as a place where customers can find all kinds of items. They do so because recommendations given by other customers have been published after they have used the product. Those customers will have experience about the product. From the customers their view of how is the product usage has been collected. This is used in recommendations. In the Proposed system, customer’s views are used for recommendations. While new customer search products, old users views are published for the particular product. On getting the customer views, one user can trust it since common people have more confidence on words-of other people. Based on product, users are given form to fill their views.On getting views, Ratings are calculated from it. These kind of recommender system give useful recommendations since we collect views of people who are familiar with the item or product. Index Terms: Recommender system, E-Commerce, collaborative filtering, Customer reviews
The document discusses sentiment analysis of customer feedback on restaurant reviews. It provides background on how sentiment analysis is used to analyze opinions expressed in online reviews and social media posts. It then describes the methodology used in the study, which involves collecting restaurant review data, preprocessing it by cleaning data and reducing attributes, and then classifying the reviews using a naive Bayes classifier to predict if sentiments expressed are positive, negative, or neutral. The goal is to design a text analysis system to automatically classify large amounts of restaurant review data using machine learning techniques.
IRJET- Physical Design of Approximate Multiplier for Area and Power EfficiencyIRJET Journal
This document summarizes research on using statistical measures and machine learning techniques to perform sentiment analysis on product reviews. The researchers collected product review data from online sources and analyzed the sentiment and opinions expressed in the text using support vector machine classifiers. They classified reviews as positive or negative and analyzed key product features that were discussed. The results demonstrated that statistical sentiment analysis can help companies better understand customer feedback and identify popular product versions or attributes. Several related works applying techniques like naive Bayes, lexicon-based methods and aspect-based sentiment analysis on reviews from domains like movies, hotels and restaurants are also summarized.
Providing Highly Accurate Service Recommendation over Big Data using Adaptive...IRJET Journal
This document proposes an adaptive recommendation system to provide accurate service recommendations over big data. It combines content-based, item-based, and knowledge-based recommendation techniques using an adaptive collaborative filtering approach. The system aims to improve scalability, accuracy, and address cold-start problems. It uses clustering to group similar services together to reduce data size and improve recommendation accuracy. The system architecture includes administrative and visitor modules to manage products and provide recommendations respectively. Service recommendations are generated by matching users to similar neighborhoods based on item preferences.
The document describes a proposed online food ordering system. Some key points:
1. The system would allow customers to easily order food from restaurants and mess services through a mobile app. Customers could browse food menus and place orders.
2. Restaurant owners and mess services would be able to update their menus and receive orders and customer feedback in real-time through the system.
3. The proposed system aims to overcome limitations of existing food ordering systems like inaccurate paper-based systems. It would provide a more convenient and efficient ordering experience for both customers and businesses.
Unlock your website's potential with a powerful UX audit in 2024! This guide explores UX audits, user experience audits, UX audit reports, and everything in between.
IRJET- Customer Buying Prediction using Machine-Learning Techniques: A SurveyIRJET Journal
1) The document discusses using machine learning techniques to predict customer purchasing and churn based on their personal and behavioral data.
2) It reviews several machine learning algorithms that have been used for prediction, including random forest, logistic regression, naive bayes, and support vector machines.
3) Deep learning techniques are also discussed, including the use of convolutional neural networks to reveal hidden patterns in customer data and predict purchases and churn.
Recommender System- Analyzing products by mining Data StreamsIRJET Journal
This document discusses several papers related to recommender systems and analyzing products and reviews. It discusses using data mining techniques like SVM, Naive Bayes and clustering algorithms to build recommendation systems for small businesses based on product sales and reviews. It also discusses detecting fake reviews using language analysis and summarizes papers on using Power BI for data visualization and analyzing research data. Key aspects covered include using data streams to provide recommendations in real-time, detecting fake reviews, using data visualization tools like Power BI for analysis, and combining clustering and association rule mining for recommendations.
Today there is a lot of buzz around customer experience. Many companies have realized that investments in customer experience improvement is important not just because it helps to boost the bottom lines of their businesses but because it takes at least 4 to 6 times more cost to acquire a new customer than to retain an existing customer.
Similar to UPSERVE – Restaurant Sales and Analysis System (20)
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
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This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
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Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.