Behavior-Based Collective Classification in Sparsely Labeled Networks
نویسندگان
چکیده
منابع مشابه
Leveraging Label-Independent Features for Classification in Sparsely Labeled Networks: An Empirical Study
We address the problem of within-network classification in sparsely labeled networks. Recent work has demonstrated success with statistical relational learning (SRL) and semi-supervised learning (SSL) on such problems. However, both approaches rely on the availability of labeled nodes to infer the values of missing labels. When few labels are available, the performance of these approaches can d...
متن کاملSLAC: A Sparsely Labeled Dataset for Action Classification and Localization
This paper describes a procedure for the creation of large-scale video datasets for action classification and localization from unconstrained, realistic web data. The scalability of the proposed procedure is demonstrated by building a novel video benchmark, named SLAC (Sparsely Labeled ACtions), consisting of over 520K untrimmed videos and 1.75M clip annotations spanning 200 action categories. ...
متن کاملColumn Networks for Collective Classification
Relational learning deals with data that are characterized by relational structures. An important task is collective classification, which is to jointly classify networked objects. While it holds a great promise to produce a better accuracy than noncollective classifiers, collective classification is computational challenging and has not leveraged on the recent breakthroughs of deep learning. W...
متن کاملCase-Based Collective Classification
This is the first paper on textual case-based reasoning to employ collective classification, a methodology for simultaneously classifying related cases that has consistently attained higher accuracies than standard classification approaches when cases are related. Thus far, case-based classifiers have not been examined for their use in collective classification. We introduce Case-Based Collecti...
متن کاملLearning Collective Behavior in Multi - Relational Networks
With the rapid expansion of the Internet and WWW, the problem of analyzing social media data has received an increasing amount of attention in the past decade. The boom in social media platforms offers many possibilities to study human collective behavior and interactions on an unprecedented scale. In the past, much work has been done on the problem of learning from networked data with homogene...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2017
ISSN: 2169-3536
DOI: 10.1109/access.2017.2723433