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Enabling Efficient and Scalable Service Search in IoT with Topic Modelling: an evaluation

M.A. Razzaque
2021 IEEE Access  
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

Wahyu Wibowo, Hugh E. Williams
2002 Proceedings of the 2002 ACM symposium on Document engineering - DocEng '02  
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

Wahyu Wibowo, Hugh E. Williams
2002 Proceedings of the 2002 ACM symposium on Document engineering - DocEng '02  
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

Afnan Al-Subaihin, Federica Sarro, Sue Black, Licia Capra
2019 Empirical Software Engineering  
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]

Samira Ghodratnama
2021 arXiv   pre-print
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

Layth Rafea, Abdulrahman Ahmed, Wisam D. Abdullah
2021 Indonesian Journal of Electrical Engineering and Computer Science  
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]

Javier Sevilla Salcedo, M. A. Quispe-Flores, Sara Carrasco-Martínez, Jaime González-Jiménez, José Carlos Castillo, Álvaro Castro-González, María Malfaz, Miguel Ángel Salichs
2021 XLII JORNADAS DE AUTOMÁTICA : LIBRO DE ACTAS  
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

Richard T. Freeman, Hujun Yin
2004 Neural Networks  
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

S. Logeswari, K. Premalatha
2015 International Journal of Telemedicine and Clinical Practices  
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

Pravin Shinde, Sharvari Govilkar
2015 International Journal on Natural Language Computing  
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

Adel R. Alharbi, Mohammad Hijji, Amer Aljaedi
2021 IET Networks  
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

Amy J. C. Trappey, Charles V. Trappey, Tzu-An Chiang, Yi-Hsuan Huang
2013 International Journal of Production Research  
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

Ke Ma, Rudrajeet Pal, Eva Gustafsson
2018 International Journal of Production Research  
. 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

Illhoi Yoo, Xiaohua Hu, Il Yeol Song
2007 International Journal of Bioinformatics Research and Applications  
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

Parvathi P.
2020 International Journal for Research in Applied Science and Engineering Technology  
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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