Student Information Chat Bot System

 

Objective

   The objective Student Information Chat Bot System paves a way to introduce a system that makes its users to have their doubts by means of querying. This system uses the AI that allows the user to get solutions for their questions.

Project Overview

     Now days, many software based applications has been designed with a great user interfaces. These interfaces can be in various formats such as command line based interface, web based application, graphical based application, voice based interface.  The interfaces that based on Web and graphical are most widely using applications in this human environment. So the need for introduction of new interface has been aroused to act as alternative choice. Finally, an interface that based on chat rooms named chat bot has developed in order to provide connectivity concurrently, the complexity that depends on multi-threading, detailing executions of services around the environment. This chat room will helpful for many areas such as business, colleges, schools, etc…This brings out the environment that paves a way for everyone in particular organization or any such thing to have their staffs digitally in single place. For instance, Manager will solve the problems regarding management by inquiring the issues through this chat bot surrounding. This reduces the travelling or visiting time, or any inquiry timings. Because bringing out all staffs in a specifically named area is difficult process, since not everyone may feel that it is convenient rime. These types of chat rooms will void the usage of menus in phones, delaying, and communication over mail etc. Chat bot acts as environment that allows to user to have their queries that may be regarding anything. This proposed system not uses any language specifically in order to interact with users.

 Proposed System

     The chat bot system introduces the areas where the people will interact and get solutions. Having the environment that one paves a path to chat bot system users. That path may be based on querying and answering. Introduced chat bot system will provide an interface that depends on text. This allows the users to type the commands and receive the text. It also involves receiving end may be having response as text to the speech.It uses the state ful based services which could remember the commands that previously asked that may be conversation.This system is developed in order to enhance the functionality.It allows the different set of people to be organizing in a specified space in order to make their discussion. The technology named chat bot can be highly utilized by large set of people in their working environment. This mechanism has developed by using Artificial based algorithms that allows the people to input their queries. Queries can be taken by chat bot and it has been analysed and understudied. There is no specific format for inputting the queries. The answers for every query has been provided since the system had used advance technology namely Artificial Intelligence. Answers would be appropriate, in case if user found that the provided answer as invalid they can make select over invalid answer. This way allows the admin to view that invalid one and to delete it. It can be deleting by admin and the admin would add relevant answer to that particular question. Finally it also helpful for student in case of their inquiry, update of their information, activities or events of college etc…

Software Requirements

• Windows 7 and above
• SQL 2008
• Visual studio 2010

Hardware Requirements

• Processor – i3
• Hard Disk – 5 GB
• Memory – 1GB RAM

Technology Used

• Artificial Intelligence

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Price Negotiator E commerce Chat Bot System

Objective

     Price Negotiator E commerce Chat Bot System introduced a system that makes the e-commerce sites to have their works in efficient manner. This E commerce Chat Bot System project would helps to automate the online selling and negotiation based on price of product. 

Project Overview

            Now days, people are looking for a technology or E commerce Chat Bot System to do their wishes in effective manner. In ancient days, people were traveled and purchase the product from the shops. But it seems to be very difficult for everyone to make their purchase over the product. Because life of human is fully engage with their busy schedule.  With their busy days, people are in need of system that brings the product at their door step in order to simple their purchase. Thus e commerce websites has been developed and act as emerging technique in this current world. People made their purchasing after the introduction the e commerce websites in efficient manner. But while come in to an online purchasing the quality and price of the product is very important. Even though things we want are getting easier, still all people are very conscious in quality and rate of the particular product. Having a best price which is not a fixed one will increase the payoff among sellers and buyers. Thus an automated agent for negotiation has been designed in order to maintain a flexible and considerable price instead of fixed price. This Automated agent will help the organization or shops to have their selling in online as automatic. It also helps the customers to negotiate the AI Bot based on price of every product. Once after the negotiation of price, the link for payment will be sent to mail in order to take the cc payments. Finally payment success has been intimated through mail. Still this mechanism involves various steps it will have many advantages over price negotiation.

Proposed System

   An agent based E commerce Chat Bot System has been developed in order to help the e commerce websites to take over a best service. This enables the e commerce sites to maintain a flexible price instead of having fixed one. Due to these flexible available prices, the payoffs of buyers and the sellers have been increased. Thus it acts a very effective mechanism for business oriented areas.

Using the three various approaches especially working for automatic negotiation, agent based negotiation has been developed automatically. Approaches namely decision theory, game theory and analysis over negotiation. This mechanism is only an emerging technologies, it is not fully developed still it has some difficulties. The issues are ontology, strategy of events, protocol used for communication. In the field of electronic commerce, electronic negotiation is an important area when come for research. To support electronic negotiation,multi attributive based utility theory has used. Valuable base learning resources are provided by the successful experience of traditional followed negotiation of human.  This strategy involves automation in online based selling and it brings the advantages to users or consumer’s to negotiate the product rate based on AI Bot. After negotiation applied, the link for specific payment has been sent to consumer or user mail. This allows the user or customer to take the payment in the manner of cc. At last email confirmation has been provided to expose the success of payment.        

Software Requirements

• Windows 7 or higher.
• SQL 2008
• Visual studio 2010

Hardware Requirements

• Processor – i3
• Hard Disk – 5 GB
• Memory – 1GB RAM
• Internet Connection

Technology Used

• Artificial Intelligence

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Document Level Sentiment Analysis Using Opinion Mining

 

Objective

            This Document Level Sentiment Analysis system aims to develop a system using opinion mining on the document analysis. This opinion mining is used for extracting the useful data from the context. The various classifications are performed for effective analysis of the sentiment.

Project Overview

      Document Level Sentiment Analysis also known as opinion mining is employed for extracting the knowledgeable information from raw set of data. The opinion mining is the greatly used method in many micro-blogging sites for the analysis of the user sentiment. It uses the Natural language Processing (NLP) and text analysis for gaining the information. The document analysis in opinion mining involves the evaluation of the overall text of a document.  Sentiment analysis provides a way for analyzing the polarity of the content. The various processes have been performed for the analysis of the content. The contents are broken and are classified as positive, negative and neutral sentiments. This classification in opinion mining helps for effective outcome. The scanning of the entire document is also performed in this process. The keywords are the vital key used for analyzing the sentiment. The ranking system is providing based on the key used to estimate the sentiment of the document.

Proposed System

      The Document Level Sentiment Analysis using opinion mining is used for extraction of the user sentiment on the document. The document comprises of textual data. The data in the form of words are stored in the database. The textual data are broken such that the analysis can be performed easier. The following are the various modules involved in the analysis of the document.

• Data pre-processing
• Classification
• Sentiment analysis

The data in the form of document are stored in the database. The data pre-processing the first step involved in which the unwanted data like duplication of entries and missing values will be eliminated. It also removes the stop words and special characters in the pre-processing methodology. The Parts of speech which are considered to provide inappropriate outcome is also removed in this process. The next step involved in the opinion mining is the classification of the sentiment. The context of the document is classified as positive, negative and neutral based on the input provided. The input document comprises of pre-determined positive and negative words against which the data from the document is matched. The keyword is used for search and the word containing keyword will be displayed based on the ranking provides to the document. The scanning of the document is performed for better results. The final process of the opinion mining is the sentiment analysis in which the result of analysis is displayed. The outcome will determine the contextual polarity of the document based on various criterion. This Document Level Sentiment Analysis system only takes the text as input. The opinion mining result will be estimating the standard of the document as a whole.

Software Requirements

• Windows OS
• WAMP Serve
• My SQL

Hardware Requirements

• Hard Disk – 1 TB or Above
• RAM required – 8 GB or Above
• Processor – Core i3 or Above

Technology Used

• Data Mining
• Sentiment Analysis

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Higher Education Access Prediction Software

 

Objective

    The Higher Education Access Prediction system aims to make the admission exams easier for the students and intimate them with the list of colleges based on their ranking. This prediction of higher education in data mining paves a greater way in education.

Project Overview

    Higher Education Access Prediction is a tool that gains the spotlight worldwide at all-time. Many technologies are brought into existence based on the education such as e-learning, smart learning and brain storms and so on. In this line of education, higher education prediction always demands a place for which a method should be implemented. This portal aims to make the online exams for admission easier and also aims to list of colleges available to students based on the market. This system enables to provide the results instantly after the examination. The questions will be provided in the format of multiple choice questions which makes it easier for the students. It also allows verifying the answers and producing the results and reducing the time and costing for processing. The human errors that are occurring at some cases can be eliminated. This system demands a constant internet connection and proper inputs for processing. This implementation of this system can be in schools and colleges and in institutions where exams are occurring frequently.

Proposed System

This Higher Education Access Prediction system aims to provide better prediction of education by means of data mining. The authority for adding questions and solution to the database is maintained by the admin. The answers are marked by the user based on the questions. The Artificial intelligence is used for verifying the answers. Then the list of colleges will be notified to the students based on their output. This Higher Education Access Prediction system also allows users to provide the feedback by the users which could be used for further development. This system comprises of two modules namely,

• Admin login
• Candidate login

The authorization is provided by means of admin. Admin login comprises of various sub categories namely, adding streams, colleges, maintaining the data base, add questions, view answers and have a look upon the feedbacks. The sub category stream contains complete details about every stream. The questions added will be in the multiple choice format and the students can post their queries and feedback in this portal.

The candidate who is taking exams must first register themselves in the portal. Same as that of admin login also comprises of various sub categories in it. The sub modules involve registration taking test, view marks, result and posting feedback. The registration process obtains complete details from the candidate like name, nationality, stream, college, gender, age, preferences and so on. The data obtained from the users will be stored in the database for future use. The test can be of various levels in order to analyse the standard knowledge of the people. Thus this Higher Education Access Prediction system makes the prediction easier.

 Software Requirements

• Windows Xp, Windows 7(ultimate, enterprise)
• Sql 2005
• Visual studio 2008

 Hardware Components

• Processor – i3
• Hard Disk – 5 GB
• Memory – 1GB RAM

Technology Used

• Data Mining
• Machine learning
• Artificial intelligence

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Movie Success Prediction Using Data Mining

 

Objective

The main aim of Movie Success Prediction Using Data Mining PHP is to propose a system that helps to predict the success of movies. This will predict whether the movie has been flop or hit or super hit based on various algorithms of data mining.

Project Overview

Now days, movies occupies a great rolein a world. Even in life of common people, movies play a significant part as internet. Thus movies have large influence in entertainment area among the public. Thus the influence of movies could leads to some goodness and badness. Movies might always focus on social issues, current political cases, spreading of awareness related to specific things etc…. For an educated or mature audience, movies could reflect unknown scenarios of society.Even thoughmovies bring out as many good things to society it also provides some bad things too. So it is necessary to identify which movie could teaches the best thing and which one is not good to take up. With the help of reviews that were made by movie viewer it is easy to decide whether that movie has hit or flop or super hit. This identification process has been carried with the help of data mining based mechanisms. A system has been designed to assign the weights and it develops the mathematically related models to predict the success of movies. For this, ancient data sets which are relate to the parameters that help for movie success has been used. By applying various mechanisms which are available in data mining fields the particular movie is identified as good or bad. This system would particularly helpful for organizations whose works on review conducting. This helps to avoid the false rating as well as better analyses over those reviews.

Proposed System

    The proposed Movie Success Prediction system aims to predict the success of particular movie based on data mining technologies that are highly employed. This system uses the data set of the post that was made by viewers of movies. Algorithm has been developed in order to predict the success rate of a specific movie. In first step, parameters has been identified that enhances the movie success and weights are assigned. Thus prediction of success paves a way to design the model mathematically in order to automate the process. Finally, the performance has been evaluated. In addition, it is found that some ratings and predictions may exactly right but some were not correct. The term close means that the bin value which has predicted is adjacent to bin having actual value. Due to this, some movies has been predicted incorrectly. For example those movies with user rating of about 7 has rate as 6 more often. Thus confusion matrices are structured with the help of rating in order to bringing out misclassification.  Incorrect and correct classifications were reported for each and every test data. Additionally correct or incorrect distance has identified based on the values that are noted as true.It includes the bins for classification that contains user ratings and gross earnings orderly in to make prediction accurately. On the other hand, approach named Support Vector Machine has also been used to obtain these same results.

Software Requirements

• Windows 7 or higher
• WAMP Server
• Notepad++
• My SQL 5.6

Hardware Requirements

• Processor – Dual Core
• Hard Disk – 50 GB
• Memory – 1GB RAM

Technology Used

• Data Mining

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Fake Product Review Monitoring and Removal for

Genuine Online Product Reviews Using Opinion Mining

Objective

     The objective of paper named Fake Product Review Monitoring and Removal for Genuine Online Product Reviews Using Opinion Mining helps to identify the cheating in reviews about product. Data mining mechanisms has been used to find out the fake reviews.

Project Overview

      Now day’s human life is fully enclosed with various busy activities. As compared to ancient days, people are doing many works but it is found that it is digitally based. Today, people are like to do their needs in very easy ways. Because everyone is surrounds by the busy environment. For instance, even humans have no time to purchase the products that they want by directly visiting the shop. People around the world were looking for simpler technology that paves a way for door step purchasing. This door step based purchasing will decreases the direct visiting of shop to purchase. Thus it increases the usage of this system among the people. The proposed system introduced the e-commerce website which helps the customers to take over their purchasing. In e-commerce websites, every user has their unique profile in order to place a unique order. In that user will search for the products and can view the reviews for those products. These reviews will help the buyers to ensure the quality of product and helps them to choose the best one.  But the truth is that this review for every product could not helpful for customers to choose the right one. Because those reviews might be fake one which was not sure in last few years. This result in to development of a system named fake product review monitoring and removal to find out the fake reviews using data mining algorithms.

Proposed Fake Product Review Monitoring

   The proposed Fake Product Review Monitoring system brings out the technology which helps to find out the review that made for product is true or not. The reason for introducing this Monitoring and removing system is to purchase the required products in a best manner. Because fake reviews also been added by owner or seller of that particular product. Users or customers of the product cant able to find these types of reviews. So proposed system would identify the fake kind of reviews based on the IP address of users. Firstly, the user will log in to their account and will do purchase the products as they wants. While reviews are added by users, the IP address is made to be noted. If many reviews are received from same IP address, that would be intimated to administrator. Then the administrator is allowed to remove those reviews that are added in fake manner. This process of tracking the IP address has been taking over by data mining technologies. Finally this methodology helps to identify the correct review. Using the trustworthy reviews one can able to buy the best and wishful products. Providing good products enhance the good reviews and better sales. This system also paves a way to bring out the best turnover for the sellers.

 Software Requirements

• Windows and above
• SQL
• Visual studio 2010

Hardware Requirements

• Processor – i3
• Hard Disk – 5 GB
• Memory – 1GB RAM

Technology Used

• Data Mining

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