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Topic Modeling To Contextualize Event-Based Datasets
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Advances on Resilient and Intelligent Cities, 2019Colombia suffered civil conflict for over five decades resulting in thousands of deaths and kidnappings and millions of displaced citizens. A peace process between the government and the Revolutionary Armed Forces of Colombia (FARC) was negotiated in 2016.
Sara Y. Del Valle +3 more
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Topic-Constrained Hierarchical Clustering for Document Datasets
2010In this paper, we propose the topic-constrained hierarchical clustering, which organizes document datasets into hierarchical trees consistant with a given set of topics. The proposed algorithm is based on a constrained agglomerative clustering framework and a semi-supervised criterion function that emphasizes the relationship between documents and ...
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A Performance Evaluation of Correlated and Dynamic Topic Modeling on a QA Dataset
2019 3rd International conference on Electronics, Communication and Aerospace Technology (ICECA), 2019Topic modeling is a set of algorithms which is used to mine the data that is hidden inside a large collection of documents. In this paper we discusses about the Correlated topic modeling and dynamic topic modeling in detail and comparing their performance on a question answer dataset based on autism.
Latha Parameswaran +2 more
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ConvAI Dataset of Topic-Oriented Human-to-Chatbot Dialogues
2018This paper contains the description and the analysis of the dataset collected during the Conversational Intelligence Challenge (ConvAI) which took place in 2017. During the evaluation round we collected over 4,000 dialogues from 10 chatbots and 1,000 volunteers.
Vadim Polulyakh +4 more
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A topic detection method for high dimensional datasets
2014Topics extraction from documents has become increasingly important due to its effectiveness in many tasks, including information retrieval, information filtering and organization of document collections in digital libraries. The Topic Detection consists to find the most significant topics within a document corpus.
AMATO, FLORA +2 more
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2020
The number of scientific publications is constantly growing to make their processing extremely time-consuming. We hypothesized that a user-defined literature tracking may be augmented by machine learning on article summaries. A specific dataset of 671 article abstracts was obtained and nineteen binary classification options using machine learning (ML ...
Yuriy N. Orlov +5 more
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The number of scientific publications is constantly growing to make their processing extremely time-consuming. We hypothesized that a user-defined literature tracking may be augmented by machine learning on article summaries. A specific dataset of 671 article abstracts was obtained and nineteen binary classification options using machine learning (ML ...
Yuriy N. Orlov +5 more
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Clustering and Visualizing Audiovisual Dataset on Mobile Devices in a Topic-Oriented Manner
2007With the significant enhancement of telecom bandwidth and multimedia-supported mobile devices occupying the market, consuming audiovisual contents on the move is no longer a hype. A lot of telecom operators are now porting traditional TV service to PDAs, 3G cell phones. However, several surveys suggest that direct migration of service from large screen
Wang, Lei +2 more
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Classification of Medical Dataset Along with Topic Modeling Using LDA
2018Nowadays, medical applications need a lot of storage for storing and providing access to the medical information seekers. Moreover in medical applications, information grows tremendously and hence they must be stored using a suitable storage structure so that it is possible to retrieve them faster from the text corpus in which the medical information ...
K. Kulothungan +5 more
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LDA Topic Modeling Based Dataset Dependency Matrix Prediction
2019Classification of text based datasets has many applications in the field of Computer Science. Some of the key application areas include scientific article recommendation, news article tagging, multimedia content search assistance, etc. We are interested in the problem of data placement of text based datasets in a distributed storage system. Distributed
Hindol Bhattacharya +3 more
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ArPod2.0: A Novel Arabic Podcast Dataset for Spoken Topic Identification
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