http://localhost:8080/xmlui/handle/123456789/2927 Tue, 23 Jun 2026 06:27:59 GMT 2026-06-23T06:27:59Z http://localhost:8080/xmlui/handle/123456789/3555 Title: Audio Opinion Mining and Sentiment Analysis of Customer Product or Services Reviews Authors: Rane, Archana L; Kshatriya, Ankita R Abstract: Sentimental analysis evolved over last few decades is only focused on textual sentimental analysis. In Internet era, people are exchanged their opinions publicly. And it is a challenge to understand and identify the context or tone of them. Another problem is that hard to categorize when the context is not given, as they could be tag positive or negative. People can be contradictory in their statements. Most reviews will have both positive and negative comments, which is somewhat manageable by analyzing sentences one at a time. However, with the help of natural language processing and computer we can categorize it. But when peoples are given their opinion in audio format then it is quiet difficult to analyze into sentiments. In this paper, we proposed the audio opinion mining and sentiment analysis of customer products or services reviews which helps to take decision in today’s business world to improve their growth of the business. Customer discrimination and sentiment analysis is performed on customer reviews collected as audio messages on customer products or services. In this paper, we proposed the audio opinion mining and sentiment analysis of customer products or services reviews which helps to take decision in today’s business world to improve their growth of the business. Customer discrimination and sentiment analysis is performed on customer reviews collected as audio messages on customer products or services. Fri, 15 Oct 2021 00:00:00 GMT http://localhost:8080/xmlui/handle/123456789/3555 2021-10-15T00:00:00Z http://localhost:8080/xmlui/handle/123456789/3547 Title: Voice Control Elevator for Prevention of Physical Touch Authors: Rane, Archana L; Patil, Nikhil Abstract: Nowadays, usage of the elevator is very common everywhere in out day to day life. The main aim of elevator is to transport the things like person or goods in fraction of seconds. As it has number of advantages so we prefer to use elevator. But as you know, corona virus is spreading all over the world; it is important and mandatory to take precaution by individual and we are sure our propose system help you out in this. The existing elevators can be used by pressing floor number as per needs. These elevators cannot be used by paralyzed, blind and physically challenged persons. In this paper we proposed voice control to elevator to prevent a physical touch as we all as all types of user can be used it easily. We used Arduino Uno ATmega328P microcontroller, Bluetooth module HC-05 and Motor driver unit with Android application. The speech recognition system provides the communication mechanism between the user and the Arduino based elevator control mechanism. We used of a DC motor for moving the elevator based on the voice/speech commands given by the user from mobile application. Its process the data and the result are generated in form of according to the user choices; that is elevator is moves upside or downside. Mon, 14 Dec 2020 00:00:00 GMT http://localhost:8080/xmlui/handle/123456789/3547 2020-12-14T00:00:00Z http://localhost:8080/xmlui/handle/123456789/3545 Title: Optimal Association Rule Mining for Web Page Prediction using Hybrid Heuristic Trained Neural Network Abstract: Today, data mining, which is a branch of web mining acts a fundamental role in diverse applications like health care data extraction, education system, search engines for evaluating their performance rank over other systems. Web Page prediction (WPP) is a classification issue in which the prediction of web pages is accomplished that a user may visit according to the knowledge of the formerly visited pages. WPP problem can be extended and implemented to reduce the access time while surfing the websites. The need to anticipate the needs of the website users to improve accessibility and user engagement is more than apparent now a day. Association rule mining is one of the most significant fields in data mining and knowledge discovery in databases. This paper plans to implement a new web page prediction model using an improved machine learning algorithm. The proposed web page prediction involves three phases (a) Rule Mining, (b) Optimal Rule Selection, and (c) Prediction. Initially, the collected web data is subjected to rule mining process. It is performed using the renowned association rule mining called Apriori algorithm, which is adopted for mining the frequent item set and association rule learning over relational databases. The length of the rule extracted from the Apriori algorithm is long, and it is needed to be reduced for performing the prediction with unique informative rules. Hence, the optimal rule selection is adopted, which uses the hybrid optimization algorithm with the integration of Deer Hunting Optimization Algorithm (DHOA) and Chicken Swarm Optimization (CSO) called Deer Hunting Rooster-based CSO (DR-CSO). Further, the optimally selected rules are subjected to the Machine learning algorithm named Neural Network (NN) for predicting the browsing behavior of the user. Along with the optimal rule extraction, the proposed DR-CSO is used for performing the training in NN. The experimental and comparative results will prove the efficiency of the developed model over existing algorithms. Mon, 15 Jun 2020 00:00:00 GMT http://localhost:8080/xmlui/handle/123456789/3545 2020-06-15T00:00:00Z http://localhost:8080/xmlui/handle/123456789/3538 Title: Biogeography optimization algorithm based next web page prediction using weblog and web content features Authors: Gangurde, Roshan A; Kumar, Binod Abstract: Recommendation of web page as per users’ interest is a broad and important area of research. Researcher adopts user behavior from actions present in cookies, logs and search queries. This paper has utilized a prior webpage fetching model using web page prediction. For this purpose, web content in form of text and weblog features are analyzed. As per dynamic user behavior, proposed model LWPP-BOA (Logistic Web Page Prediction By Biogeography Optimization Algorithm) predict page by using genetic algorithm. Based on user actions, weblog feature are developed in form of association rules, while web content gives a set of relevant text patterns. Page prediction as per random user behavior is enhanced by means of Biogeography Optimization Algorithm where crossover operation is performed as per immigration and emigration values. Here population updation depends on other parameters of chromosome except fitness value. Experiments are conducted on real dataset having web content and weblogs. Results are compared using precision, coverage, M-Metric, MAE and RMSE parameters and it indicates that the proposed work is better than other approaches already in use. Wed, 10 Jun 2020 00:00:00 GMT http://localhost:8080/xmlui/handle/123456789/3538 2020-06-10T00:00:00Z