An overview of topic modeling methods and tools
BV Barde, AM Bainwad - 2017 International Conference on …, 2017 - ieeexplore.ieee.org
Topic modeling is a powerful technique for analysis of a huge collection of a document.
Topic modeling is used for discovering hidden structure from the collection of a document …
Topic modeling is used for discovering hidden structure from the collection of a document …
Modeling law search as prediction
Law search is fundamental to legal reasoning and its articulation is an important challenge
and open problem in the ongoing efforts to investigate legal reasoning as a formal process …
and open problem in the ongoing efforts to investigate legal reasoning as a formal process …
[PDF][PDF] User based aggregation for biterm topic model
Abstract Biterm Topic Model (BTM) is designed to model the generative process of the word
co-occurrence patterns in short texts such as tweets. However, two aspects of BTM may …
co-occurrence patterns in short texts such as tweets. However, two aspects of BTM may …
Enhancing topic clustering for Arabic security news based on k‐means and topic modelling
The internet has become one of the main sources of news spread as it unleashed the
information dissemination space, where the news websites express opinions on entities …
information dissemination space, where the news websites express opinions on entities …
Rater-effect IRT model integrating supervised LDA for accurate measurement of essay writing ability
M Uto - Artificial Intelligence in Education: 20th International …, 2019 - Springer
Essay-writing tests are widely used in various assessment contexts to measure higher-order
abilities of learners. However, a persistent difficulty is that ability measurement accuracy …
abilities of learners. However, a persistent difficulty is that ability measurement accuracy …
[HTML][HTML] Recent advances in bibliometric indexes and the PaperRank problem
P Amodio, L Brugnano - Journal of Computational and Applied …, 2014 - Elsevier
Bibliometric indexes are customary used in evaluating the impact of scientific research, even
though it is very well known that in different research areas they may range in very different …
though it is very well known that in different research areas they may range in very different …
Supervised topic models with word order structure for document classification and retrieval learning
One limitation of most existing probabilistic latent topic models for document classification is
that the topic model itself does not consider useful side-information, namely, class labels of …
that the topic model itself does not consider useful side-information, namely, class labels of …
LIMTopic: a framework of incorporating link based importance into topic modeling
Topic modeling has become a widely used tool for document management. However, there
are few topic models distinguishing the importance of documents on different topics. In this …
are few topic models distinguishing the importance of documents on different topics. In this …
A hierarchy method based on LDA and SVM for news classification
He growth of the online data provides the user a access to information on the Internet but
also creates the challenges to obtain the valuable knowledge. In this paper we focus on …
also creates the challenges to obtain the valuable knowledge. In this paper we focus on …
[PDF][PDF] Increasing serendipity of recommender system with ranking topic model
Z Xiao, F Che, E Miao, M Lu - Applied Mathematics & …, 2014 - naturalspublishing.com
There are thousands of academic paper published each year, it is quite hard for researchers
who enters a new field to discover relevant paper and novel paper to read, which we …
who enters a new field to discover relevant paper and novel paper to read, which we …