Modeling and Data Mining in Blogosphere: Synthesis Lectures on Data Mining and Knowledge Discovery
Autor Nitin Agarwal, Huan Liuen Limba Engleză Paperback – 22 iul 2009
Din seria Synthesis Lectures on Data Mining and Knowledge Discovery
- 20% Preț: 176.93 lei
- 20% Preț: 345.67 lei
- 20% Preț: 325.73 lei
- 20% Preț: 351.34 lei
- 20% Preț: 347.28 lei
- 20% Preț: 379.22 lei
- 20% Preț: 376.15 lei
- 20% Preț: 379.68 lei
- 20% Preț: 220.40 lei
- 20% Preț: 219.43 lei
- 20% Preț: 163.23 lei
- 20% Preț: 217.96 lei
- 20% Preț: 224.46 lei
- 20% Preț: 224.92 lei
- 20% Preț: 292.51 lei
- 20% Preț: 199.72 lei
- 20% Preț: 162.07 lei
- 20% Preț: 174.36 lei
- 20% Preț: 321.04 lei
- 20% Preț: 376.30 lei
- Preț: 399.13 lei
Preț: 164.82 lei
Preț vechi: 206.02 lei
-20% Nou
Puncte Express: 247
Preț estimativ în valută:
31.56€ • 33.11$ • 26.18£
31.56€ • 33.11$ • 26.18£
Carte tipărită la comandă
Livrare economică 27 ianuarie-10 februarie 25
Preluare comenzi: 021 569.72.76
Specificații
ISBN-13: 9783031007705
ISBN-10: 3031007700
Ilustrații: IX, 127 p.
Dimensiuni: 191 x 235 mm
Greutate: 0.25 kg
Editura: Springer International Publishing
Colecția Springer
Seria Synthesis Lectures on Data Mining and Knowledge Discovery
Locul publicării:Cham, Switzerland
ISBN-10: 3031007700
Ilustrații: IX, 127 p.
Dimensiuni: 191 x 235 mm
Greutate: 0.25 kg
Editura: Springer International Publishing
Colecția Springer
Seria Synthesis Lectures on Data Mining and Knowledge Discovery
Locul publicării:Cham, Switzerland
Cuprins
Modeling Blogosphere.- Blog Clustering and Community Discovery.- Influence and Trust.- Spam Filtering in Blogosphere.- Data Collection and Evaluation.
Notă biografică
Nitin Agarwal is a professor of Information Science at University of Arkansas at Little Rock. He received his Bachelor of Technology in Information Technology from Indian Institute of Information Technology, India, and Ph.D. in Computer Science from Arizona State University. He is one of the founding members of the Social Computing group in the Data Mining and Machine Learning Lab at ASU. His primary research interests include Social Computing, Knowledge Extraction in Social Media, Modeling Influence, Collective Wisdom, Familiar Strangers, and Model Evaluation. His work has resulted in publications in various prestigious forums including book chapters, encyclopedia entries, conferences and journals. His presentation at Web Search and Data Mining (WSDM 2008) conference on "Identifying the Influential Bloggers in a Community" recorded the highest number of hits (over 700) among all the talks at the conference. He co-presented a tutorial at the premiere data mining conference KDD 2008 on "Blogosphere: Research Issues, Applications, and Tools." He is a co-guest editor of a special issue on "Social Computing in Blogosphere" for IEEE Internet Computing magazine appearing (2010).Huan Liu is a professor of Computer Science and Engineering at Arizona State University. He received his Bachelor of Engineering from Shanghai Jiao Tong University and Ph.D. from University of Southern California, researched at Telecom Research Labs in Australia, and taught at National University of Singapore before he joined ASU. He has been recognized for excellence in teaching and research in CSE, ASU. His research interests are in data/web mining, machine learning, social computing, and artificial intelligence, investigating problems that arise in many real-world applications with high-dimensional data of disparate forms such as social media, modeling group interaction, text categorization, biomarker identification, and text/web mining. His research is sponsored by NSF, NASA, AFOSR, and ONR, among others. His well-cited publications include books, book chapters, encyclopedia entries as well as conference and journal papers. He serves on journal editorial boards and numerous conference program committees, and is a founding organizer of the International Workshop Series on Social Computing, Behavioral Modeling, and Prediction in Phoenix, AZ (SBP'08 and SBP'09). His professional memberships include AAAI, ACM, ASEE, and IEEE.