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MB-ToT: An Effective Model for Topic Mining in Microblogs
2014
Applied Mathematics & Information Sciences
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Topic mining on microblogging sites with sheer scale of instance messages and social network information, such as Twitter, is a hard and challenging problem. ...
Firstly, we assume each topic is a mixture distribution influenced by both word co-occurrences and timestamps of microblogs. This allows MB-ToT to capture the changes of each topic over time. ...
Sun, Large scale microblog mining using distributed MB-LDA, Proceedings of the 21st international conference companion on World Wide Web, New York: ACM Press, 1035-1042 (2012). [9] X. Meng, F. ...
doi:10.12785/amis/080137
fatcat:knw4rqmpozczpimrgb7oftso4a
CLDA: An Effective Topic Model for Mining User Interest Preference under Big Data Background
2018
Complexity
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LDA is an effective method of text mining, but it will not play a very good role in applying LDA directly to a large number of short texts in microblog. ...
We mainly use a large number of user text data from microblog to study. ...
MB-LDA: it is a generative model based on LDA for theme mining on Weibo [31, 32] . ...
doi:10.1155/2018/2503816
fatcat:ydushel7kzbpfhzmafc76w7il4
TM-ToT: An Effective Model for Topic Mining from the Tibetan Messages
[chapter]
2014
Communications in Computer and Information Science
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The microblog platforms, such as Weibo, now accumulate a large scale of data including the Tibetan messages. ...
In our experiments, TM-ToT outperforms Twitter-LDA by a large margin in terms of perplexity. Furthermore, the quality of the generated latent topics of TM-ToT is promising. ...
[7] introduced a novel probabilistic generative model MicroBlog-Latent Dirichlet Allocation (MB-LDA) for large scale microblog mining. ...
doi:10.1007/978-3-662-45924-9_40
fatcat:d7iq4d7s2ze75nsy5yyysjaqti
Design and Implementation of Parallelized LDA Topic Model Based on MapReduce
2018
DEStech Transactions on Computer Science and Engineering
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In order to solve theefficiency bottlenecksof non-parallel LDA topic model while processing large-scale text datasets,a parallel LDA topic model computing framework based on MapReduce is designed and implemented ...
Performance testing of the parallel LDA topic modelis also conducted by using the bibliographic sample data of articles and patents.Experiment shows that, the parallel LDA topic analysis process based ...
Zhang Chenyi et al [3] proposed a microblog generation model MB-LDA which based on LDA for topic mining of microblog texts. ...
doi:10.12783/dtcse/ccnt2018/24712
fatcat:lr5u3o3m55dwdlaoz3f3tdkyr4
Heat Analysis of Entrepreneurial Hotspots
2017
DEStech Transactions on Computer Science and Engineering
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of microblog for topic mining [11] . ...
Nowadays, LDA model has been widely used, for example, Chen-yi Zhang et al. proposed the microblog generation model MB-LDA which took into account the contact association and text association relationship ...
doi:10.12783/dtcse/cst2017/12543
fatcat:fdzdsahezvaolnvjmw3wduydry
Weibo clustering: A new approach utilizing users' reposting data in social networking services
2014
Computer Science and Information Systems
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A modified model called "MB-LDA" is proposed on topic mining in [27] , which introduces the "@" and "RT" (Retweet, Repost) into the LDA model to mine the latent relations in the conversations whose test ...
Although the experimental results show this method works well on large-scale microblog dataset, the small length of news in microblog cannot ensure completeness of the whole event. ...
doi:10.2298/csis130927070z
fatcat:mddm5i4drjfl3mdlm43ah4wucq
A Prerecognition Model for Hot Topic Discovery Based on Microblogging Data
2014
The Scientific World Journal
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When adopting topic detection and tracking techniques to find hot topics with streamed microblogging data, it will meet obstacles like streamed microblogging data clustering, topic hotness definition, ...
The microblogging is prevailing since its easy and anonymous information sharing at Internet, which also brings the issue of dispersing negative topics, or even rumors. ...
And then a parallel clustering algorithm should be provided to process large scale of posts. ...
doi:10.1155/2014/360934
pmid:25254235
pmcid:PMC4164368
fatcat:w723pmih3jhxzi5gmrtdhf4ihq
Extracting Actionable Knowledge from Domestic Violence Discourses on Social Media
[article]
2018
arXiv
pre-print
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But, it is difficult to mine the actionable knowledge from large conversational datasets from social media due to the characteristics of high dimensions, short, noisy, huge volume, high velocity, and so ...
But, it is challenging for the information retrieval from the large streams of microblogs of its following characteristics: • Immense scale of volume, fast data arriving rate and their unique characteristics ...
On variation of LDA, online-LDA [41] , Dynamic topic models [40] , labelled LDA [42] used probabilistic topic models as a baseline model to detect events in twitter streams. ...
arXiv:1807.02391v1
fatcat:sg7uaofqdzddjd3derap23lyie
Extracting Actionable Knowledge from Domestic Violence Discourses on Social Media
2018
EAI Endorsed Transactions on Scalable Information Systems
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But, it is difficult to mine the actionable knowledge from large conversational datasets from social media due to the characteristics of high dimensions, short, noisy, huge volume, high velocity, and so ...
But, it is challenging for the information retrieval from the large streams of microblogs of its following characteristics: • Immense scale of volume, fast data arriving rate and their unique characteristics ...
On variation of LDA, online-LDA [41] , Dynamic topic models [40] , labelled LDA [42] used probabilistic topic models as a baseline model to detect events in twitter streams. ...
doi:10.4108/eai.29-5-2018.154807
fatcat:kvgaqlzvxnc7xou4upc5tmrehq
Constructing Topic Models of Internet of Things for Information Processing
2014
The Scientific World Journal
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Therefore, constructing high quality topic hierarchies that can capture the term distribution of each product record enables us to better understand users' search intent and benefits tasks such as taxonomy ...
MB-LDA [12] is designed for topic mining of microblogs or tweets, which takes both contact relation and document relation into consideration. ...
We make use of two large-scale datasets for the evaluation of our model, both of which are extracted from real-world data sources. ...
doi:10.1155/2014/675234
pmid:25110737
pmcid:PMC4119721
fatcat:4hxligtscnhdtjc7uibqyqdqom
A big data methodology for categorising technical support requests using Hadoop and Mahout
2014
Journal of Big Data
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proposes a Proof of Concept (PoC) end to end solution that utilises the Hadoop programming model, extended ecosystem and the Mahout Big Data Analytics library for categorising similar support calls for large ...
While research associated with machine learning algorithms is well established, research on big data analytics and large scale distributed machine learning is very much in its infancy with libraries such ...
Research design and methodology The proposed solution provides an end to end solution for conducting large scale analysis of technical support data using the open source Hadoop platform, components of ...
doi:10.1186/2196-1115-1-1
fatcat:2xhb6n5a5fcghe5egy3baow3py
Bursty event detection from microblog: a distributed and incremental approach
2015
Concurrency and Computation
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In this paper, we propose a distributed and incremental temporal topic model for microblogs called Bursty Event dEtection (BEE+). ...
With the rise in popularity and size of microblogs, there is a need for distributed approaches that can detect bursty event with low latency from the short-text data stream. ...
INTRODUCTION Bursty Event dEtection (BEE+) from microblogs is now a hot area in the field of data mining and knowledge discovery, because the information posted in microblogs is real time and often event ...
doi:10.1002/cpe.3657
fatcat:uhwzwh6iqngc5pgrqr23bc623y
Open challenges for data stream mining research
2014
SIGKDD Explorations
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This article presents a discussion on eight open challenges for data stream mining. ...
The resulting analysis is illustrated by practical applications and provides general suggestions concerning lines of future research in data stream mining. ...
to thank the participants of the RealStream2013 workshop at ECMLPKDD2013 in Prague, and in particular Bernhard Pfahringer and George Forman, for suggestions and discussions on the challenges in stream mining ...
doi:10.1145/2674026.2674028
fatcat:y3bozzeohveibgxb5wmiwfcogm
Topic-Level Opinion Influence Model(TOIM): An Investigation Using Tencent Micro-Blogging
[article]
2012
arXiv
pre-print
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To evaluate and test this proposed model, an experiment was designed and a sub-dataset from Tencent Micro-Blogging was used. ...
Mining user opinion from Micro-Blogging has been extensively studied on the most popular social networking sites such as Twitter and Facebook in the U.S., but few studies have been done on Micro-Blogging ...
Topic Model based Sentiment Analysis and Opinion Detection Since the introduction of LDA model [23] , various extended LDA models have been proposed for topic extraction from large-scale corpora. ...
arXiv:1210.6497v1
fatcat:rjp3g6jxwvemtejwgiox2zuu5m
Entropy-Enhanced Attention Model for Explanation Recommendation
2022
Entropy
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The loss function of the model is used to realize the interpretability of recommendation systems. ...
Most of the existing recommendation systems using deep learning are based on the method of RNN (Recurrent Neural Network). ...
Although it improves the effect of recommendation, the problem of data sparsity will gradually appear when the data scale is large enough. ...
doi:10.3390/e24040535
pmid:35455199
pmcid:PMC9028415
fatcat:meao2xfwzjcudf3w6ocbug2xs4
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