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Guest Editors' Introduction: Mining Actionable Knowledge on the Web
2004
IEEE Intelligent Systems
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Up to now, a great deal of work has been done applying data mining and machine learning methods to discover novel and useful knowledge on the Web. ...
T he Web-its resources and users-offers a wealth of information for data mining and knowledge discovery. ...
users to view and use. Recently, more and more work addresses mining the Web for knowledge that computer systems will use. ...
doi:10.1109/mis.2004.64
fatcat:ctwdpyxajvdrtjz7epgyo6piim
Authors Index
2021
2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)
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Images using TinyML Strategies with Transfer Learning FitNet: A deep neural network driven architecture for real time posture rectification Implementation of a WGAN-GP for Human Pose Transfer using a 3 ...
using a 3-channel pose representation Assistance System Prasanth, Senthan Constructing Global Researchers Network Using Google Scholar Profiles for Collaborator Recommendation Systems Samanta, Ashis Kumar ...
Errors in Android Programming Learning Assistance Photovoltaic Solar Power Plant Maintenance Management based on IoT and Machine Learning Yahyaoui, Amani Implementation of Web-based Interactive Learning ...
doi:10.1109/3ict53449.2021.9581857
fatcat:cstqtiz5rjg65llynoy4ehcdua
Implementation of Fund Recommendation System Using Machine Learning
2021
Journal of multimedia information system
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The future fund prices are predicted by Prophet model which is one of the machine learning methods for time series data prediction. ...
We implement web pages for the fund recommendation and for the future fund price prediction. ...
Time series prediction through machine learning Time series data means data recorded sequentially according to the passage of time. ...
doi:10.33851/jmis.2021.8.3.183
fatcat:ljphzb7lbzdsjgalnzhjzzxcwm
Reinforcement Learning to Rank
2019
Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining - WSDM '19
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Standard machine learning has helped us a lot in the singleturn paradigm, where we use it to predict: intent, relevance, user satisfaction, etc. ...
When we think of search or recommendation as a series of exchanges, we need to turn to bandit algorithms to determine which action the system should take next, or to reinforcement learning to determine ...
doi:10.1145/3289600.3291605
dblp:conf/wsdm/Rijke19
fatcat:ai4c2x425vah3jlgsptndbwuby
PagePrompter: An Intelligent Web Agent Created Using Data Mining Techniques
[chapter]
2002
Lecture Notes in Computer Science
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In this paper, we introduce a novel algorithm for creating an intelligent agent for navigating a web site based on combining web usage mining and machine learning. ...
Creating an intelligent agent for web navigation, which is an agent that dynamically gives recommendations to a web site's users by learning from web usage mining and users' behavior, is a challenge for ...
It demonstrates that data mining and machine learning can be used as knowledge acquisition methods for building intelligent agents. ...
doi:10.1007/3-540-45813-1_67
fatcat:7tkummwlz5bldarb3aojavypfq
Proposal to Improve the Management System of Storage in a Virtual Learning Environment
2021
Ciencia e Ingeniería
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The system uses artificial intelligence technologies such as machine learning and deep learning to explore strategies for optimizing how stored data is processed. ...
This article introduces a theoretical model of a storage management system for big data-based virtual learning environments. ...
Streaming and machine learning: Allows you to receive real-time data streams sent by the queuing system and new data stored in the data warehouse. These are processed together using machine learning. ...
doi:10.53766/cei/2021.43.02.09
fatcat:s5ucsictkna7bkmsr4pzgyjsr4
Book Recommendation System Using Machine Learning
2021
International Journal for Research in Applied Science and Engineering Technology
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Keywords: Recommender System, Support Vector Machine (SVM), Machine Learning, Classification etc. ...
Abstract: Users can use book recommendation systems to search and select books from a number of options available on the web or elsewhere electronic sources. ...
System Using Machine
Learning
Prof. ...
doi:10.22214/ijraset.2021.39658
fatcat:rxcqt2tvi5frnebhfgvjcw3xwe
Technical Approach in Text Mining for Stock Market Prediction: A Systematic Review
2018
Indonesian Journal of Electrical Engineering and Computer Science
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TEXT MINING IN WEB-BASED APPLICATION Web-based application much attention through web intelligence that analysed the news filtering, summary of web and news recommendation system [31] . ...
Textual Data Mining Through Machine Learning Different machine learning (M. Learning) techniques are available to use for stock market prediction [36] . E.g. GA/TDNN, ANFIS, ICA-BPN, GA/ATNN. ...
doi:10.11591/ijeecs.v10.i2.pp770-777
fatcat:n5hf2opjczdfneo5lnhtg6eske
Intelligent Web Applications as Future Generation of Web Applications
2019
Scientific Journal of Informatics
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as well as impact this application in the process development web systems. ...
In commerce, personal relationship, the effect of the universal network has wholly changed the way people interact with each other and with machines. ...
Machine Learning refers to an enabling technology, which enables web applications to get used to with time via observation and learning from habits of the users, their preferences and idiosyncrasies. ...
doi:10.15294/sji.v6i2.19297
fatcat:hzkchuz46zg4fcmgcnljibqwle
A Data Mining and Analysis Platform for Investment Recommendations
2021
Electronics
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The modules are: analysis and data mining, the forecasting system, the technical analysis module, the recommender system, and the visualization platform. ...
Moreover, the proposal includes a visualization platform for high-level interaction between the user and the recommender system. ...
Highlighted the need for historical stock market data after reviewing various machine learning techniques for stock prediction. [3] The author provided a mixed approach that uses both machine learning ...
doi:10.3390/electronics10070859
fatcat:mlxe52khunghrlu3ko7lox2fw4
Toward Social Media Content Recommendation Integrated with Data Science and Machine Learning Approach for E-Learners
2020
Symmetry
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There is much e-learning software available—for example, LMS (Learning Management System) and Moodle. ...
For recommendations, a Reinforcement learning model with optimization is employed, which utilizes the learners' local context, learners' profile available in the e-learning system, and the learners' historical ...
Similarly, the reinforcement learning-based social media content recommendation system is to use data mining and machine learning approach to improve the accuracy of social media content recommendation ...
doi:10.3390/sym12111798
fatcat:wfgccritmjgn7lopmy7yz7dxna
Toward Improving the Prediction Accuracy of Product Recommendation System Using Extreme Gradient Boosting and Encoding Approaches
2020
Symmetry
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We have evaluated Mean Absolute Error, Mean Square Error, and Root Mean Square Error for our proposed methodology and also other machine learning algorithms. ...
The proposed algorithm relies on combining extreme gradient boosting machine learning architecture with word2vec mechanism to explore the purchased products based on the click patterns of users. ...
The collaborate filtering algorithm was used for recommendation systems. The XGBoost machine learning algorithm was used for the classification and prediction process. ...
doi:10.3390/sym12091566
fatcat:rdq4ygtktvhabbzv5s32v6kdk4
Design of a recommendation system based on collaborative filtering and machine learning considering personal needs of the user
2019
Eastern-European Journal of Enterprise Technologies
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E-commerce turns to Machine Learning to improve recommendations for consumers as regular/potential visitors of a Web-resource. ...
The result of implementing practical part of the current work is the designed system in the form of "VikToMovie" Web application -a recommendation system on movies based on the Machine Learning hybrid ...
doi:10.15587/1729-4061.2019.175507
fatcat:lq2avvq455hkbkcpafyl25kunq
Developed High Scale Bagging Algorithm for E-Tourism Advising System
2022
Al-Salam Journal for Engineering Science and Technology
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Machine learning techniques are the most suitable to deal with such big data. ...
One of the applications that can be implemented in machine learning is a tourist advising system that harvests data from tourism sites and aggregates different types of data about them (humidity, temperature ...
SYSTEM IMPLEMENTATION The tourist advising system uses machine learning and bagging algorithm in the back end as mentioned earlier, while the user can input his/her preference through a user-friendly web ...
doi:10.55145/ajest.2022.01.01.005
fatcat:squr3qunvrgr3c4ndmpdzx6ja4
Crop Selection using IoT and Machine Learning
2020
International Journal for Research in Applied Science and Engineering Technology
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We developed a model of 'CROP SELECTION USING IOT AND MACHINE LEARNING' which helps farmers to select the best crop for their farmland. ...
The used dataset consists of parameters like crop name, temperature, humidity and soil ph. ...
Using the values, the machine learning model will retrieve some crops which are suitable to the agricultural land and provided to the farmers using a web application.
II. ...
doi:10.22214/ijraset.2020.30462
fatcat:vq3fehjocjgfjk2ci5mb3oxs4y
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