Advances in Knowledge Discovery and Data Mining - Bookswagon
Home > Computer & Internet > Databases > Information retrieval > Advances in Knowledge Discovery and Data Mining
Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining


     0     
5
4
3
2
1



International Edition


About the Book

Social Networks and Social Media.- Maximizing Friend-Making Likelihood for Social Activity Organization.- What Is New in Our City? A Framework for Event Extraction Using Social Media Posts.- Link Prediction in Aligned Heterogeneous Networks.- Scale-Adaptive Group Optimization for Social Activity Planning.- Influence Maximization Across Partially Aligned Heterogeneous Social Networks.- Multiple Factors-Aware Diffusion in Social Networks.- Understanding Community Effects on Information Diffusion.- On Burst Detection and Prediction in Retweeting Sequence.- Few Things About Idioms: Understanding Idioms and Its Users in the Twitter Online Social Network.- Retweeting Activity on Twitter: Signs of Reception.- Resampling-Based Gap Analysis for Detecting Nodes with High Centrality on Large Social Network.- Classification.- Double Ramp Loss Based Reject Option Classifier.- Efficient Methods for Multi-label Classification.- A Coupled k-Nearest Neighbor Algorithm for Multi-label Classification.- Learning Topic-Oriented Word Embedding for Query Classification.- Reliable Early Classification on Multivariate Time Series with Numerical and Categorical Attributes.- Distributed Document Representation for Document Classification.- Prediction of Emergency Events: A Multi-Task Multi-Label Learning Approach.- Nearest Neighbor Method Based on Local Distribution for Classification.- Immune Centroids Over-Sampling Method for Multi-Class Classification.- Optimizing Classifiers for Hypothetical Scenarios.- Repulsive-SVDD Classification.- Centroid-Means-Embedding: an Approach to Infusing Word Embeddings into Features for Text Classification.- Machine Learning.- Collaborating Differently on Different Topics: A Multi-Relational Approach to Multi-Task Learning.- Multi-Task Metric Learning on Network Data.- A Bayesian Nonparametric Approach to Multilevel Regression.- Learning Conditional Latent Structures from Multiple Data Sources.- Collaborative Multi-view Learning with Active Discriminative Prior for Recommendation.- Online and Stochastic Universal Gradient Methods for Minimizing Regularized Hölder Continuous Finite Sums in Machine Learning.- Context-Aware Detection of Sneaky Vandalism on Wikipedia Across Multiple Languages.- Uncovering the Latent Structures of Crowd Labeling.- Use Correlation Coefficients in Gaussian Process to Train Stable ELM Models.- Local Adaptive and Incremental Gaussian Mixture for Online Density Estimation.- Latent Space Tracking from Heterogeneous Data with an Application for Anomaly Detection.- A Learning-Rate Schedule for Stochastic Gradient Methods to Matrix Factorization.- Applications.- On Damage Identification in Civil Structures Using Tensor Analysis.- Predicting Smartphone Adoption in Social Networks.- Discovering the Impact of Urban Traffic Interventions Using Contrast Mining on Vehicle Trajectory Data.- Locating Self-collection Points for Last-mile Logistics using Public Transport Data.- A Stochastic Framework for Solar Irradiance Forecasting Using Condition Random Field.- Online Prediction of Chess Match Result.- Learning of Performance Measures from Crowd-Sourced Data with Application to Ranking of Investments.- Hierarchical Dirichlet Process for Tracking Complex Topical Structure Evolution and its Application to Autism Research Literature.- Automated Detection for Probable Homologous Foodborne Disease Outbreaks.- Identifying Hesitant and Interested Customers for Targeted Social Marketing.- Activity-Partner Recommendation.- Iterative Use of Weighted Voronoi Diagrams to Improve Scalability in Recommender Systems.- Novel Methods and Algorithms Principal Sensitivity Analysis.- SocNL: Bayesian Label Propagation with Confidence.- An Incremental Local Distribution Network for Unsupervised Learning.- Trend-Based Citation Count Prediction for Research Articles.- Mining Text Enriched Heterogeneous Citation Networks.- Boosting via Approaching Optimal Margin Distribution.- o-HETM: An Online Hierarchical Entity Topic Model for


Best Sellers



Product Details
  • ISBN-13: 9783319180373
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Depth: 51
  • Height: 234 mm
  • No of Pages: 763
  • Series Title: Lecture Notes in Computer Science
  • Sub Title: 19th Pacific-asia Conference, Pakdd 2015
  • Width: 156 mm
  • ISBN-10: 3319180371
  • Publisher Date: 22 Apr 2015
  • Binding: Paperback
  • Edition: 2015 ed.
  • Language: English
  • Returnable: Y
  • Spine Width: 40 mm
  • Weight: 1146 gr


Similar Products

Add Photo
Add Photo

Customer Reviews

REVIEWS      0     
Click Here To Be The First to Review this Product
Advances in Knowledge Discovery and Data Mining
Springer -
Advances in Knowledge Discovery and Data Mining
Writing guidlines
We want to publish your review, so please:
  • keep your review on the product. Review's that defame author's character will be rejected.
  • Keep your review focused on the product.
  • Avoid writing about customer service. contact us instead if you have issue requiring immediate attention.
  • Refrain from mentioning competitors or the specific price you paid for the product.
  • Do not include any personally identifiable information, such as full names.

Advances in Knowledge Discovery and Data Mining

Required fields are marked with *

Review Title*
Review
    Add Photo Add up to 6 photos
    Would you recommend this product to a friend?
    Tag this Book Read more
    Does your review contain spoilers?
    What type of reader best describes you?
    I agree to the terms & conditions
    You may receive emails regarding this submission. Any emails will include the ability to opt-out of future communications.

    CUSTOMER RATINGS AND REVIEWS AND QUESTIONS AND ANSWERS TERMS OF USE

    These Terms of Use govern your conduct associated with the Customer Ratings and Reviews and/or Questions and Answers service offered by Bookswagon (the "CRR Service").


    By submitting any content to Bookswagon, you guarantee that:
    • You are the sole author and owner of the intellectual property rights in the content;
    • All "moral rights" that you may have in such content have been voluntarily waived by you;
    • All content that you post is accurate;
    • You are at least 13 years old;
    • Use of the content you supply does not violate these Terms of Use and will not cause injury to any person or entity.
    You further agree that you may not submit any content:
    • That is known by you to be false, inaccurate or misleading;
    • That infringes any third party's copyright, patent, trademark, trade secret or other proprietary rights or rights of publicity or privacy;
    • That violates any law, statute, ordinance or regulation (including, but not limited to, those governing, consumer protection, unfair competition, anti-discrimination or false advertising);
    • That is, or may reasonably be considered to be, defamatory, libelous, hateful, racially or religiously biased or offensive, unlawfully threatening or unlawfully harassing to any individual, partnership or corporation;
    • For which you were compensated or granted any consideration by any unapproved third party;
    • That includes any information that references other websites, addresses, email addresses, contact information or phone numbers;
    • That contains any computer viruses, worms or other potentially damaging computer programs or files.
    You agree to indemnify and hold Bookswagon (and its officers, directors, agents, subsidiaries, joint ventures, employees and third-party service providers, including but not limited to Bazaarvoice, Inc.), harmless from all claims, demands, and damages (actual and consequential) of every kind and nature, known and unknown including reasonable attorneys' fees, arising out of a breach of your representations and warranties set forth above, or your violation of any law or the rights of a third party.


    For any content that you submit, you grant Bookswagon a perpetual, irrevocable, royalty-free, transferable right and license to use, copy, modify, delete in its entirety, adapt, publish, translate, create derivative works from and/or sell, transfer, and/or distribute such content and/or incorporate such content into any form, medium or technology throughout the world without compensation to you. Additionally,  Bookswagon may transfer or share any personal information that you submit with its third-party service providers, including but not limited to Bazaarvoice, Inc. in accordance with  Privacy Policy


    All content that you submit may be used at Bookswagon's sole discretion. Bookswagon reserves the right to change, condense, withhold publication, remove or delete any content on Bookswagon's website that Bookswagon deems, in its sole discretion, to violate the content guidelines or any other provision of these Terms of Use.  Bookswagon does not guarantee that you will have any recourse through Bookswagon to edit or delete any content you have submitted. Ratings and written comments are generally posted within two to four business days. However, Bookswagon reserves the right to remove or to refuse to post any submission to the extent authorized by law. You acknowledge that you, not Bookswagon, are responsible for the contents of your submission. None of the content that you submit shall be subject to any obligation of confidence on the part of Bookswagon, its agents, subsidiaries, affiliates, partners or third party service providers (including but not limited to Bazaarvoice, Inc.)and their respective directors, officers and employees.

    Accept

    New Arrivals



    Inspired by your browsing history


    Your review has been submitted!

    You've already reviewed this product!