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Enabling Efficient and Scalable Service Search in IoT with Topic Modelling: an evaluation
2021
IEEE Access
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In this paper, we identify these issues and quantitatively and qualitatively evaluate how well a set of selected short textsspecific topic modelling approaches perform as IoT service categorisers against ...
A categorisation of these services into their application domains can reduce the search space and offer an efficient and scalable service search. ...
An adaptive and less strict condition might allow more than one topics in a document/service description and support hierarchical categorisation. Further research is necessary for this direction. ...
doi:10.1109/access.2021.3071009
fatcat:qxrbtgb4irc4dkcigpiwdduukq
Simple and accurate feature selection for hierarchical categorisation
2002
Proceedings of the 2002 ACM symposium on Document engineering - DocEng '02
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Categorisation of digital documents is useful for organisation and retrieval. ...
We show that a good hierarchical machine learningbased categoriser can be developed using small numbers of features from pre-categorised training documents. ...
In this paper, we use machine learning-based linear similarity categorisers to address the automatic categorisation problem and a word model to represent documents. ...
doi:10.1145/585058.585079
dblp:conf/doceng/WibowoW02
fatcat:ormnpvukp5bl5k2aes7yzy26wm
Simple and accurate feature selection for hierarchical categorisation
2002
Proceedings of the 2002 ACM symposium on Document engineering - DocEng '02
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Categorisation of digital documents is useful for organisation and retrieval. ...
We show that a good hierarchical machine learningbased categoriser can be developed using small numbers of features from pre-categorised training documents. ...
In this paper, we use machine learning-based linear similarity categorisers to address the automatic categorisation problem and a word model to represent documents. ...
doi:10.1145/585076.585079
fatcat:hdlc7qqqibhdvcfu763bguzuf4
Empirical comparison of text-based mobile apps similarity measurement techniques
2019
Empirical Software Engineering
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However, a better quality can be achieved using a good feature extraction technique and a traditional clustering method. ...
Objective In this paper, we investigate different techniques to compute the similarity of apps based on their textual descriptions and evaluate their effectiveness using hierarchical agglomerative clustering ...
What is the Clustering Performance at Different Granularity Levels for Each Technique? Hierarchical clustering affords the user a range of possible k values. ...
doi:10.1007/s10664-019-09726-5
fatcat:5qocj35arfhlrhuctplurg22lq
Towards Personalized and Human-in-the-Loop Document Summarization
[article]
2021
arXiv
pre-print
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approaches, and (iv) the need for reference summaries. ...
The ubiquitous availability of computing devices and the widespread use of the internet have generated a large amount of data continuously. ...
; and the hierarchical structured self-attentive model for extractive document summarisation (HSSAS) [111] is a neural network model with a hierarchical structured self-attention mechanism to create ...
arXiv:2108.09443v2
fatcat:245c3byhg5htrnmbnoofexzh3u
Classification of a COVID-19 dataset by using labels created from clustering algorithms
2021
Indonesian Journal of Electrical Engineering and Computer Science
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In this paper, the hierarchical and k-means clustering techniques are used to create a tool for identifying similar articles on COVID-19 and filtering them based on their titles. ...
Results show that the proposed tool effectively extracts the keywords for each cluster, with RF, DT and bagging achieving optimal accuracies of 98.267%, 97.633% and 97.833%, respectively.</span> ...
ACKNOWLEDGEMENTS This work was funded by the Allen Institute for AI, which prepared the CORD-19 dataset in partnership with leading research groups, and Kaggle, which hosted the COVID-19 Open Research ...
doi:10.11591/ijeecs.v21.i1.pp164-173
fatcat:qrl3526k25b6lfvx22viw6swui
Dynamic semantic ontology generation: a proposal for social robots
[chapter]
2021
XLII JORNADAS DE AUTOMÁTICA : LIBRO DE ACTAS
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Applied to social robotics, it could lead to a natural and fluid human-robot interaction. ...
Semantic knowledge could be a solution by structuring information according to its meaning and its semantic associations. ...
Hotho, they redefined the model extraction step and focused on ontology-based document clustering, introducing a new development in text pre-processing be- Figure 2 : A taxonomy of clustering approaches ...
doi:10.17979/spudc.9788497498043.557
fatcat:p3fyovz6wfguzdxfnq4hnec5cu
Adaptive topological tree structure for document organisation and visualisation
2004
Neural Networks
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A review is also given on the existing neural network based methods for document clustering and organisation. ...
The results demonstrate the advantages of the proposed validation criteria and the efficiency of the ATTS approach for document organisation, visualisation and search. ...
The average F-measure for retrieving most relevant documents from clusters for the ATTS, bisecting k-means and SOM. ...
doi:10.1016/j.neunet.2004.08.006
pmid:15555865
fatcat:il7yl4t5lrgajh2sdnobbpf7ay
Ontology-based semantic smoothing model for biomedical document clustering
2015
International Journal of Telemedicine and Clinical Practices
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It is a mixture of simple language model and a topic signature translation model. ...
In this work ontology-based semantic smoothing model is proposed which uses the domain ontology for concept extraction. ...
Document clustering plays a vital role in real world applications of information retrieval domain, for example, grouping the web search results and categorising digital documents. ...
doi:10.1504/ijtmcp.2015.069475
fatcat:mnmnhfgs6rec3jk3tdbhy5thje
A Systematic study of Text Mining Techniques
2015
International Journal on Natural Language Computing
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The techniques that are used to analyse these intermediate representations such as clustering, distribution analysis, association rules and visualisation of the results. ...
Text mining involves the pre-processing of document collections such as information extraction, term extraction, text categorization, and storage of intermediate representations. ...
Text categorisation and IE enable users to move from a "machine readable" representation of the documents to a "machine understandable" form of the documents. ...
doi:10.5121/ijnlc.2015.4405
fatcat:pv6lawef7ngvzc7xwnf5aaj4ou
Enhancing topic clustering for Arabic security news based on k‐means and topic modelling
2021
IET Networks
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As shown in the experiments' results, our proposed combined method has a high round index rate of 87.2%, with a large number of topics and clusters. ...
Our experiments validate the k-means clustering algorithm with and without the latent Dirichlet allocation topic modelling method, and we adopted various validation techniques to measure the topic clustering ...
| Topics hierarchical clustering In hierarchical clustering, the algorithm categorises the items (the topics in our case) into a hierarchy analogous to a treelike structure called a dendrogram. ...
doi:10.1049/ntw2.12017
fatcat:4nh44p7iczhxzmybyaimoopdd4
Ontology-based neural network for patent knowledge management in design collaboration
2013
International Journal of Production Research
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and practical references for the collaborative networks of technology-centric product and production development teams. ...
This research develops a novel knowledge management approach using ontology-based artificial neural network (ANN) algorithm to automatically classify and search knowledge documents stored in huge online ...
The authors thank the editors and reviewers for their valuable comments and suggestions for the manuscript revision. ...
doi:10.1080/00207543.2012.701775
fatcat:ho74wwqfy5fxbkw7kpedaqtg2a
What modelling research on supply chain collaboration informs us? Identifying key themes and future directions through a literature review
2018
International Journal of Production Research
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. 380 articles employing modelling approach where collaboration forms the core of analysis were screened for hierarchical cluster analysis, resulting in four clusters: information sharing paradigm, joint ...
Textmining technology and conceptual criteria were used to categorise and screen articles into different categories. Finally, cluster analysis was used to group articles and identify emerging themes. ...
most important aspects considered for subsequent categorisation and cluster analysis. ...
doi:10.1080/00207543.2018.1535204
fatcat:q5742nek7rdk7cnef7tsiyxvme
Biomedical ontology improves biomedical literature clustering performance: a comparison study
2007
International Journal of Bioinformatics Research and Applications
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Document clustering has been used for better document retrieval and text mining. ...
For this investigation, we perform a comprehensive comparison study of various document clustering approaches such as hierarchical clustering methods, Bisecting K-means, K-means and Suffix Tree Clustering ...
NSF CCF 0514679 and the PA Department of Health Tobacco Settlement Formula Grant (#240205, 240196). ...
doi:10.1504/ijbra.2007.015010
pmid:18048199
fatcat:lhtzgq4owbclrd7dye5r22ax4u
An Analysis of Short Text Detection and Classification Algorithms
2020
International Journal for Research in Applied Science and Engineering Technology
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We take conceptual information as a sort of data and incorporate it into deep neural networks. Here we are going to study different methods available for text classification and categorisation. ...
In recent years, there has been an exponential growth within the number of complex documents and texts. ...
Having a better system for categorisation of documents for this information requires understanding these algorithms. ...
doi:10.22214/ijraset.2020.6026
fatcat:7ewkxwlggjef3n7t67qrbvt3ay
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