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Research on LAK Algorithm for Short Text Topic Detection

Aijun Li, Tong Chang
2019 DEStech Transactions on Computer Science and Engineering  
In this paper, we propose a LAK algorithm for short text topic detection. In the algorithm, the probability distribution of topic-words is obtained by the Latent Dirichlet Allocation model.  ...  The effectiveness of LAK algorithm in topic detection is proved by experiments. 1  ...  Then Yin J et al. proposed a new clustering topic detection method, which divided the topic detection into two stages: local topic phase and global topic phase, and used the global topic model to perform  ... 
doi:10.12783/dtcse/iciti2018/29098 fatcat:h5cxkf22tba5rhj7rdwfql4mlu

Topic Detection and Tracking Based on Windowed DBSCAN and Parallel KNN

Chuanzhen Li, Minqiao Liu, Juanjuan Cai, Yang Yu, Hui Wang
2020 IEEE Access  
An improved density-based spatial clustering of application with noise (DBSCAN) clustering algorithm based on the time window is proposed to achieve accurate topic detection with the auxiliary advantage  ...  In this paper, a topic detection system driven by big data is built on the Spark platform, which aims at improving the efficiency of news collecting from the Internet and improving the accuracy and efficiency  ...  hot topic detection algorithm.  ... 
doi:10.1109/access.2020.3047458 fatcat:hkv7ezerrrcohpszwpixcmrxoa

Domain-oriented Topic Discovery Based on Features Extraction and Topic Clustering

Xiaofeng Lu, Xiao Zhou, Wenting Wang, Pietro Lio, Pan Hui
2020 IEEE Access  
Topic detection technology can automatically discover new topics on the Internet.  ...  This paper investigates domain-oriented feature extraction methods, and proposes a keyword feature extraction method ITFIDF-LP, a subject word feature extraction method LDA-SLP and a topic clustering model  ...  Researchers focus on hot topics detection by finding new features and improving topic clustering algorithms.  ... 
doi:10.1109/access.2020.2994516 fatcat:2ohfx2fsr5fufkjj3r7bdhnrzq

Concept-Based Topic Model Improvement [chapter]

Claudiu Musat, Julien Velcin, Marian-Andrei Rizoiu, Stefan Trausan-Matu
2011 Studies in Computational Intelligence  
We propose a system which employs conceptual knowledge to improve topic models by removing unrelated words from the simplified topic description.  ...  Results obtained on two different corpora in different test conditions show that the words detected as unrelated had a much greater probability than the others to be chosen by human evaluators as not being  ...  The results show clearly that the algorithm follows human intuition and that improving topics in this manner is feasible.  ... 
doi:10.1007/978-3-642-22732-5_12 fatcat:uwj76d7y7ref7dhdoasoxwshw4

Constructing of Multimedia Resources for Second Language Teaching Based on Intelligent Information Processing of Movie Resources

Hua Liu
2013 International Journal of Emerging Technologies in Learning (iJET)  
Based on the topic models database and time density of caption's dialogue, designed a adaptive, iterative incremental learning algorithm, which could meanwhile carry out topic detection, words clustering  ...  and calculating words' used degree.  ...  Overall algorithm of topic detection and word clustering of heuristic, iterative and incremental learning 1.  ... 
doi:10.3991/ijet.v8i5.3045 fatcat:ijsyfxj7zjev5c4knajsl7vnbu

A Novel Sentence Embedding Based Topic Detection Method for Microblogs

Cong Wan, Shan Jiang, Cong Wang, Ying Yuan, Cuirong Wang
2020 IEEE Access  
(3) How to use microblog relation structure to improve performance? In this paper, we present a novel two step approach to resolve topic detection issues in microblogs.  ...  Experiments on realworld datasets show that attention layer and p-mean layer could improve the capability of our neural network. (2) Our clustering algorithm can detect topics correctly and find the number  ... 
doi:10.1109/access.2020.3036043 fatcat:kb3ypnemefcrtkqspwirfgjefa

SMS Phishing Detection Using Oversampling and Feature Optimization Method

Tong WU, Kang-feng ZHENG, Chun-hua WU, Xiu-juan WANG
2018 DEStech Transactions on Computer Science and Engineering  
Three types features are presented including token features, topic features and Linguistic Inquiry and Word Count (LIWC) features.  ...  Finally, the detection results are achieved by Random Forest classification algorithm.  ...  The study of detection algorithm is aimed at improving detection accuracy through various statistical learning methods and machine learning algorithms.  ... 
doi:10.12783/dtcse/iece2018/26634 fatcat:by4twiwo45glnj2w2edq266qqa

Hot Topic Detection and Analysis on Temporal Microblog Topic Model

Mei Yu, Hongyun Shang, Jian Yu, Tianyi Xu, Jie Gao, Yue Gao
2017 ICIC Express Letters  
The TMT model outperformed these non-temporal algorithms with an improved accuracy of topic detection and an excellent performance on hot topic clustering.  ...  Most existing topic detection algorithms are based on n-grams clustering techniques or latent topic detection, which lack the ability to detect topics in an "on-line" manner, since they ignore the temporal  ...  The authors gratefully acknowledge the helpful comments and suggestions of the reviewers, which have greatly improved the presentation.  ... 
doi:10.24507/icicel.11.03.625 fatcat:uykv3bcydjdcvjyxlv6shf5fae

Text Clustering Incremental Algorithm in Sensitive Topic Detection

Yuejin Zhang
2018 International Journal of Information and Communication Sciences  
In the real application, the new incremental text clustering algorithm basically meets the real-time demand of online topic detection and has a certain practical value.  ...  Make improvement to clustering algorithm according to different media types is the main research direction.  ...  Related work Topic detection derives from Topic Detection and Tracking, TDT [4, 5] . So far, the algorithm applies to topic detection mainly based on incremental clustering algorithm.  ... 
doi:10.11648/j.ijics.20180303.12 fatcat:mogrhyzjavgsviqwmzvshu3sse


Sukhpreet Kaur .
2013 International Journal of Research in Engineering and Technology  
Furthermore, a comparative analysis of two different text segmentation algorithms namely C99 and TopicTiling on image documents is presented.  ...  To assess how well each algorithm works, each was applied on different datasets and results were compared. The work done also proves the efficiency of TopicTiling over C99.  ...  The basic unit in this algorithm is a topic which can be a word or a group of words. Each unit is assigned topic id, based upon which text segmentation is done.  ... 
doi:10.15623/ijret.2013.0209080 fatcat:ipgx5man25dvvppf2blfqtb4fq

Improving Arabic Cognitive Distortion Classification in Twitter using BERTopic

Fatima Alhaj, Ali Al-Haj, Ahmad Sharieh, Riad Jabri
2022 International Journal of Advanced Computer Science and Applications  
The proposed algorithm utilizes a transformer-based topic modeling (BERTopic).  ...  It employs two types of document representations and performs averaging and concatenation to produce contextual topic embeddings.  ...  Mainly, the algorithm uses two types of document representations; topic distribution and word embedding. Then, it performs averaging and concatenation.  ... 
doi:10.14569/ijacsa.2022.0130199 fatcat:nsajjds525ealknxacjghz3aja

An Improved Topic Detection Method for Chinese Microblog Based On Incremental Clustering

Gongshen Li, Kui Meng, Jing Xie
2013 Journal of Software  
We also give an improved topic detection algorithm which uses a new vector distance calculation method and center vector updating method.  ...  The study of microblog topic detection method can help users and service providers find out microblog hot topics dynamically.  ...  To improve the efficiency of the algorithm, we only take nine kinds of words into consideration.  ... 
doi:10.4304/jsw.8.9.2313-2320 fatcat:sqziqocxrrentarwdnybvcnkva

BTM and GloVe Similarity Linear Fusion-Based Short Text Clustering Algorithm for Microblog Hot Topic Discovery

Di Wu, Mengtian Zhang, Chao Shen, Zhuyun Huang, Mingxing Gu
2020 IEEE Access  
[7] proposed a microblog hot topic detection algorithm based on two-stage clustering. The PLSA model and K-means were combined for secondary clustering to detect microblog hot topics. Zhou et al.  ...  [10] improved the LDA model and proposed a microblog hot topic detection model (FSC-LDA).  ... 
doi:10.1109/access.2020.2973430 fatcat:ieh4wsgr5zcg7lfd7dkx3xav34

Automated Duplicate Bug Report Detection Using Multi-Factor Analysis

Jie ZOU, Ling XU, Mengning YANG, Xiaohong ZHANG, Jun ZENG, Sachio HIROKAWA
2016 IEICE transactions on information and systems  
Also, the recall rate is improved by 2.96%-10.53% compared to the state-of-art approach DBTM. key words: duplicate bug reports detection, topic model, LDA, N-gram, LNG  ...  To improve the detection accuracy, in this paper, we propose a new approach calls LNG (LDA and N-gram) model which takes advantages of the topic model LDA and word-based model Ngram.  ...  The topic model LDA can detect the topic similarity between two bug reports even when they are not similar textually.  ... 
doi:10.1587/transinf.2016edp7052 fatcat:egvq2n3cszh7piowic5kpawgf4

An Improved Clustering Method for Detection System of Public Security Events Based on Genetic Algorithm and Semisupervised Learning

Heng Wang, Zhenzhen Zhao, Zhiwei Guo, Zhenfeng Wang, Guangyin Xu
2017 Complexity  
Finally, simulation experiments are conducted from two aspects of qualitative analysis and quantitative analysis, which demonstrate that the proposed algorithm performs excellently in improving clustering  ...  Then, to overcome the shortcoming of the traditional clustering algorithm, an improved fuzzy c-means (FCM) algorithm based on adaptive genetic algorithm and semisupervised learning is proposed.  ...  Xiaolin et al. proposed an improved single-pass clustering algorithm for topic detection [4] . Researches on topic detection and tracking are developing rapidly.  ... 
doi:10.1155/2017/8130961 fatcat:zzos4q3u3va4fhxhfwgichszwa
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