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Big Data Analytics and Knowledge Discovery

20th International Conference, DaWaK 2018, Regensburg, Germany, September 3–6, 2018, Proceedings

  • Conference proceedings
  • © 2018

Overview

Editors:
  1. Carlos Ordonez

    1. University of Houston, Houston, USA

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    You can also search for this editor in PubMed   Google Scholar

  2. Ladjel Bellatreche

    1. LIAS/ISAE-ENSMA, Chasseneuil-du-Poitou, France

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11031)

Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)

Included in the following conference series:

Conference proceedings info: DaWaK 2018.

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Table of contents (29 papers)

  1. Front Matter

    Pages I-XV
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  2. Graph Analytics

    1. Front Matter

      Pages 1-1
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    2. Graph BI & Analytics: Current State and Future Challenges

      • Amine Ghrab, Oscar Romero, Salim Jouili, Sabri Skhiri
      Pages 3-18

    3. Community Detection in Who-calls-Whom Social Networks

      • Ciprian-Octavian Truică, Olivera Novović, Sanja Brdar, Apostolos N. Papadopoulos
      Pages 19-33

    4. FedS: Towards Traversing Federated RDF Graphs

      • Qaiser Mehmood, Alokkumar Jha, Dietrich Rebholz-Schuhmann, Ratnesh Sahay
      Pages 34-45

  3. Case Studies

    1. Front Matter

      Pages 47-47
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    2. Adversarial Spiral Learning Approach to Strain Analysis for Bridge Damage Detection

      • Takaya Kawakatsu, Akira Kinoshita, Kenro Aihara, Atsuhiro Takasu, Jun Adachi
      Pages 49-58

    3. CoRe: Generating a Computationally Representative Road Skeleton - Integrating AADT with Road Structure

      • Rohith Reddy Sankepally, K. S. Rajan
      Pages 59-69

    4. E-Commerce Product Recommendation Using Historical Purchases and Clickstream Data

      • Ying Xiao, C. I. Ezeife
      Pages 70-82

    5. Effective Classification of Ground Transportation Modes for Urban Data Mining in Smart Cities

      • Carson K. Leung, Peter Braun, Adam G. M. Pazdor
      Pages 83-97

    6. Location Prediction Using Sentiments of Twitter Users

      • Ritu Singh, Durga Toshniwal
      Pages 98-108

  4. Classification and Clustering

    1. Front Matter

      Pages 109-109
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    2. A Clustering Model for Uncertain Preferences Based on Belief Functions

      • Yiru Zhang, Tassadit Bouadi, Arnaud Martin
      Pages 111-125

    3. A Novel Committee–Based Clustering Method

      • Sonia Fiol-Gonzalez, Cassio Almeida, Simone Barbosa, Hélio Lopes
      Pages 126-136

    4. KMN - Removing Noise from K-Means Clustering Results

      • Benjamin Schelling, Claudia Plant
      Pages 137-151

    5. Subset Labeled LDA: A Topic Model for Extreme Multi-label Classification

      • Yannis Papanikolaou, Grigorios Tsoumakas
      Pages 152-162

    6. Third Party Data Clustering Over Encrypted Data Without Data Owner Participation: Introducing the Encrypted Distance Matrix

      • Nawal Almutairi, Frans Coenen, Keith Dures
      Pages 163-173

  5. Pre-proccesing

    1. Front Matter

      Pages 175-175
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    2. An Efficient Prototype Selection Algorithm Based on Spatial Abstraction

      • Joel Luís Carbonera, Mara Abel
      Pages 177-192

    3. Web Usage Data Cleaning

      • Amine Ganibardi, Chérif Arab Ali
      Pages 193-203
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  1. Big Data Analytics and Knowledge Discovery

Keywords

About this book

This book constitutes the refereed proceedings of the 20th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2018, held in Regensburg, Germany, in September 2018.

The 13 revised full papers and 17 short papers presented were carefully reviewed and selected from 76 submissions. The papers are organized in the following topical sections: Graph analytics; case studies; classification and clustering; pre-processing; sequences; cloud and database systems; and data mining.

Editors and Affiliations

  • University of Houston, Houston, USA

    Carlos Ordonez

  • LIAS/ISAE-ENSMA, Chasseneuil-du-Poitou, France

    Ladjel Bellatreche

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