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Titlebook: Web Recommendations Systems; K. R. Venugopal,K. C. Srikantaiah,Sejal Santosh Ni Book 2020 Springer Nature Singapore Pte Ltd. 2020 Web reco

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41#
發(fā)表于 2025-3-28 17:45:37 | 只看該作者
Automatic Discovery and Ranking of Synonyms for Search Keywords in the Web,his scalable technique can be applied to online data on the dynamic, domain-independent and unstructured World Wide Web. The candidate synonyms are ranked using Co-occurrence Frequencies and various page count based measures. The experimental results show that the best results are obtained using the proposed algorithm with WebJaccard.
42#
發(fā)表于 2025-3-28 20:16:43 | 只看該作者
Web Page Recommendations Based Web Navigation Prediction,r than the traditional method which uses 30 min as default time-out. The proposed method uses standard benchmark datasets to analyse and compare our framework with two-tier prediction framework. Simulation results show that our generated classifier framework WNPWR outperforms two-tier prediction framework in prediction accuracy and time.
43#
發(fā)表于 2025-3-29 00:54:32 | 只看該作者
Web Page Recommendations Based Web Navigation Prediction,r than the traditional method which uses 30 min as default time-out. The proposed method uses standard benchmark datasets to analyse and compare our framework with two-tier prediction framework. Simulation results show that our generated classifier framework WNPWR outperforms two-tier prediction framework in prediction accuracy and time.
44#
發(fā)表于 2025-3-29 04:16:23 | 只看該作者
45#
發(fā)表于 2025-3-29 08:07:40 | 只看該作者
Advertisement Recommendations Using Expectation Maximization,chnique is used to learn hidden topics from the vocabulary. Least Absolute Shrinkage and Selection Operator (LASSO) is used to predict total number of conversions. Experiment results show that PCAEM model outperforms TopicMachine model by reducing Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) for prediction.
46#
發(fā)表于 2025-3-29 13:37:31 | 只看該作者
Web Data Extraction and Integration System for Search Engine Results,arch engines help us to narrow down the search in the form of Search Engine Result Pages (SERP). Web Content Mining is one of the techniques that help users to extract useful information from these SERPs. In this chapter, we propose two similarity-based mechanisms; Web Data Extraction using Similari
47#
發(fā)表于 2025-3-29 19:36:29 | 只看該作者
48#
發(fā)表于 2025-3-29 22:52:13 | 只看該作者
Mining and Cyclic Behaviour Analysis of Web Sequential Patterns,hat helps us to mine useful behavioural patterns and draw conclusions from them after careful analysis. Efficient Web pattern mining is a challenge taking into consideration the enormous quantities of raw Web log data and explosive growth of information in the Web. In this chapter, we propose a nove
49#
發(fā)表于 2025-3-30 01:45:47 | 只看該作者
50#
發(fā)表于 2025-3-30 06:29:05 | 只看該作者
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