Results 11 to 20 of about 443,004 (222)
Graph-Sparse LDA: A Topic Model with Structured Sparsity [PDF]
, 2014 Originally designed to model text, topic modeling has become a powerful tool for uncovering latent structure in domains including medicine, finance, and vision.
Adams, Ryan +2 more
core +1 more source
Scientific Dataset Discovery via Topic-level Recommendation
, 2021 Data intensive research requires the support of appropriate datasets. However, it is often time-consuming to discover usable datasets matching a specific research topic. We formulate the dataset discovery problem on an attributed heterogeneous graph, which is composed of paper-paper citation, paper-dataset citation, and also paper content.
Altaf, Basmah +2 more
openaire +2 more sources
Emergent Leadership Detection Across Datasets [PDF]
, 2019 Automatic detection of emergent leaders in small groups from nonverbal behaviour is a growing research topic in social signal processing but existing methods were evaluated on single datasets -- an unrealistic assumption for real-world applications in ...
Bulling, Andreas, Müller, Philipp
core +3 more sources
Scalable Topical Phrase Mining from Text Corpora
, 2014 While most topic modeling algorithms model text corpora with unigrams, human interpretation often relies on inherent grouping of terms into phrases. As such, we consider the problem of discovering topical phrases of mixed lengths.
El-Kishky, Ahmed +4 more
core +1 more source
A Semantic Graph-Based Approach for Mining Common Topics From Multiple Asynchronous Text Streams [PDF]
, 2017 In the age of Web 2.0, a substantial amount of unstructured content are distributed through multiple text streams in an asynchronous fashion, which makes it increasingly difficult to glean and distill useful information.
Guo Weiwei +6 more
core +1 more source
Investigating the performance of automatic new topic identification across multiple datasets [PDF]
Proceedings of the American Society for Information Science and Technology, 2006 AbstractRecent studies on automatic new topic identification in Web search engine user sessions demonstrated that neural networks are successful in automatic new topic identification. However most of this work applied their new topic identification algorithms on data logs from a single search engine.
Özmutlu, H. Cenk +3 more
openaire +3 more sources
Detecting Similar Linked Datasets Using Topic Modelling
, 2016 The Web of data is growing continuously with respect to both the size and number of the datasets published. Porting a dataset to five-star Linked Data however requires the publisher of this dataset to link it with the already available linked datasets.
Röder, Michael +3 more
openaire +2 more sources
Document Informed Neural Autoregressive Topic Models with Distributional Prior
, 2019 We address two challenges in topic models: (1) Context information around words helps in determining their actual meaning, e.g., "networks" used in the contexts "artificial neural networks" vs. "biological neuron networks".
Buettner, Florian +3 more
core +1 more source
2kenize: Tying Subword Sequences for Chinese Script Conversion
, 2020 Simplified Chinese to Traditional Chinese character conversion is a common preprocessing step in Chinese NLP. Despite this, current approaches have poor performance because they do not take into account that a simplified Chinese character can correspond ...
A, Pranav, Augenstein, Isabelle
core +1 more source
Using patterns position distribution for software failure detection [PDF]
, 2013 Pattern-based software failure detection is an important topic of research in recent years. In this method, a set of patterns from program execution traces are extracted, and represented as features, while their occurrence frequencies are treated as the ...
Agrawal R. +20 more
core +3 more sources