Titlebook: Information Integration and Web Intelligence; 24th International C Eric Pardede,Pari Delir Haghighi,Gabriele Kotsis Conference proceedings

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bNaming: An Intelligent Application to Assist Brand Names Definitiony of the evaluation criteria, our application automatically generated a score matching with the output given by the branding experts within a positive/negative deviation of one point in more than 80% of the cases. Finally, an MVP is developed that already presents satisfactory results.

Bernstein-test

Mining Twitter Multi-word Product Opinions with Most Frequent Sequences of Aspect Termsatures. This paper proposes a system called Microblog Aspect Sequence Miner (MASM) as an extension of Microblog Aspect Miner (MAM) by replacing the Apriori algorithm with a modified frequent sequential pattern mining algorithm based on CM-SPAM to also enable mining multi-word aspects more efficientl

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sion control, corrosion monitoring in practice, humanitarian aspects of corrosion science and technology (history of the evolution of knowledge about corrosion, relationships between corrosion and philosophy, c978-94-007-9130-5978-90-481-3477-9

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José Vieira,Rodrigo Rocha,Luis F. Pereira,Igor Vanderlei,Jean Araujo,Jamilson Dantassion control, corrosion monitoring in practice, humanitarian aspects of corrosion science and technology (history of the evolution of knowledge about corrosion, relationships between corrosion and philosophy, c978-94-007-9130-5978-90-481-3477-9

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pical country like India with vast coastline. MS corrodes relatively faster and thus leads to colossal loss in every year and to reduce this loss some kind of protection in the form of paints and coatings is al978-81-322-1709-1978-81-322-0720-7Series ISSN 1612-1317 Series E-ISSN 1868-1212

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0302-9743 organized in conjunction with 24th International Conference on Advances in Mobile Computing & Multimedia Intelligence (MoMM2022)..​The dominant research focus of submitted papers was artificial intelligence and machine learning. The accepted papers presented advances and innovations in an array of

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A Comparative Performance Analysis of Fast K-Means Clustering Algorithmsit is difficult to predict the efficiency of individual algorithms in certain application scenarios. We thus present a performance analysis of existing fast k-means algorithms. We focus on simple interpretability and comparability and abstract from many implementation details so as to provide a guide for data scientists and practitioners alike.