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Semantic Smoothing for Model-based Document Clustering
2006
IEEE International Conference on Data Mining. Proceedings
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Inspired by a series of statistical translation language model for text retrieval, we propose in this paper a novel smoothing method referred to as context-sensitive semantic smoothing for document clustering ...
The comparative experiment on three datasets shows that model-based clustering approaches with semantic smoothing is effective in improving cluster quality. [13] Zhou, X. ...
of model-based document clustering. ...
doi:10.1109/icdm.2006.142
dblp:conf/icdm/ZhangZH06
fatcat:gjstvfvc5bakbpnu7h25qjiwfi
Ontology-based semantic smoothing model for biomedical document clustering
2015
International Journal of Telemedicine and Clinical Practices
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In this work ontology-based semantic smoothing model is proposed which uses the domain ontology for concept extraction. ...
Recent researches focus on the clustering of text documents based on the semantic smoothing technique, which resolves the conflicts by general words and the sparsity of class-specific core words. ...
It comprises of two context-sensitive semantic smoothing models named document model-based and cluster model-based techniques. ...
doi:10.1504/ijtmcp.2015.069475
fatcat:mnmnhfgs6rec3jk3tdbhy5thje
Dragon Toolkit: Incorporating Auto-Learned Semantic Knowledge into Large-Scale Text Retrieval and Mining
2007
19th IEEE International Conference on Tools with Artificial Intelligence(ICTAI 2007)
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The incorporation of semantic knowledge then reduces to the smoothing of unigram language models using semantic knowledge. ...
The majority of text retrieval and mining techniques are still based on exact feature (e.g. words) matching and unable to incorporate text semantics. ...
When the dataset to cluster is small, model-based kmeans with semantic smoothing (both CSSS and CISS) not only outperform model-based k-means with Laplacian smoothing and background smoothing, but also ...
doi:10.1109/ictai.2007.117
dblp:conf/ictai/ZhouZH07
fatcat:n7oe6nms3vhphpa4f26zzoo2d4
Exploiting Image Contents in Web Search
2007
International Joint Conference on Artificial Intelligence
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We evaluate the new model-based similarity measure on three datasets using complete linkage criterion for agglomerative clustering and find out it significantly improves the clustering quality over the ...
Both problems can be resolved by suitable smoothing of document model and using Kullback-Leibler divergence of two smoothed models as pairwise document distances. ...
We also thank three anonymous reviewers for their instructive comments on the paper. ...
dblp:conf/ijcai/ZhouD07
fatcat:vemop4hxsfdufafkqladgjjzz4
Semantic v.s. Positions: Utilizing Balanced Proximity in Language Model Smoothing for Information Retrieval
2013
International Joint Conference on Natural Language Processing
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We balance the effects of semantic and positional smoothing, and score a document based on the smoothed language model. ...
Work on information retrieval has shown that language model smoothing leads to more accurate estimation of document models and hence is crucial for achieving good retrieval performance. ...
Acknowledgments This work was supported by "III Innovative and Prospective Technologies Project" of the Institute for Information Industry which is subsidized by the Ministry of Economy Affairs of the ...
dblp:conf/ijcnlp/YanJLLLL13
fatcat:fz3lz4zxgfenlcrxfrs3ao4er4
Clustering Massive Text Data Streams by Semantic Smoothing Model
[chapter]
2007
Lecture Notes in Computer Science
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In this paper, we firstly give an improved semantic smoothing model for text data stream environment. ...
Then we use the improved semantic model to improve the clustering quality and present an online clustering algorithm for clustering massive text data streams. ...
In [7] , model-based clustering approaches based on semantic smoothing that is widely used in information retrieval (IR) [8] is presented for efficient text data clustering. ...
doi:10.1007/978-3-540-73871-8_36
fatcat:5okdburf5zfybid4i4ezjvfpua
Context-sensitive semantic smoothing for the language modeling approach to genomic IR
2006
Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '06
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signature using the EM algorithm; and (3) expanding document and query models based on topic signature translations. ...
The implemented semantic smoothing models, such as the translation model which statistically maps document terms to query terms, and a number of works that have followed have shown good experimental results ...
We also thank four anonymous reviewers for their comments on the paper. ...
doi:10.1145/1148170.1148203
dblp:conf/sigir/ZhouHZLS06
fatcat:utt4jhemlvgfvnwxa5motw5xom
Clustering Text Data Streams
2008
Journal of Computer Science and Technology
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However, the existing semantic smoothing model is not suitable for dynamic text data context. In this paper, we extend the semantic smoothing model into text data streams context firstly. ...
Recently, researchers argue that semantic smoothing model is more efficient than the existing TF * IDF scheme for improving text clustering quality. ...
Acknowledgements We would like to thanks the anonymous reviewers for their helpful comments on the early version of this paper. ...
doi:10.1007/s11390-008-9115-1
fatcat:dmrzfq6nxvflhkbyzle2hl3cui
Semantic smoothing for text clustering
2013
Knowledge-Based Systems
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In this paper we present a new semantic smoothing vector space kernel (S-VSM) for text documents clustering. ...
To the best of our knowledge, the current study is the first to systematically compare, analyze and evaluate the impact of semantic smoothing in text clustering based on 'wisdom of linguists', e.g., WordNets ...
Hence, the need of smooth semantically the VSM model, i.e., by employing semantic smoothing VSM kernels, arises. ...
doi:10.1016/j.knosys.2013.09.012
fatcat:ssupj4c7engi7mhwldmpuniv7a
Tackling Sparsity, the Achilles Heel of Social Networks: Language Model Smoothing via Social Regularization
2015
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
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We propose to tackle this specific weakness of social networks by smoothing the posting document language model based on social regularization. ...
Online social networks nowadays have the worldwide prosperity, as they have revolutionized the way for people to discover, to share, and to diffuse information. ...
We thank all the anonymous reviewers for their valuable and constructive comments in ACL short paper track 1 .
References ...
doi:10.3115/v1/p15-2103
dblp:conf/acl/YanLLH15
fatcat:rqec3okenzdjpcsexdvjl5jtcu
Topic Signature Language Models for Ad hoc Retrieval
2007
IEEE Transactions on Knowledge and Data Engineering
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Document models based on topic signature translation are then derived. ...
The previously implemented semantic smoothing models, such as the translation model which statistically maps document terms to query terms, and a number of other works that have followed have shown good ...
The smoothed document models can be used not only for text retrieval, but also for many other text mining applications such as text clustering. ...
doi:10.1109/tkde.2007.1058
fatcat:maftbty6hfdorash3mu3dmetqa
A Complex Network Approach to Distributional Semantic Models
2015
PLoS ONE
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Furthermore, to simulate a semantic network with the observed network properties, we propose a new growing network model based on the model of Steyvers and Tenenbaum. ...
features of a word-context matrix and the functions of matrix weighting and smoothing. ...
As shown in
Results for Hierarchical Property SVD smoothing works differently for word-document-based and word-word-based networks. ...
doi:10.1371/journal.pone.0136277
pmid:26295940
pmcid:PMC4546414
fatcat:pfz5x3gbdrb5tkgaypz5ymif4e
More Discriminative Sentence Embeddings via Semantic Graph Smoothing
[article]
2024
arXiv
pre-print
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Leveraging semantic graph smoothing, we enhance sentence embeddings obtained from pretrained models to improve results for the text clustering and classification tasks. ...
Our method, validated on eight benchmarks, demonstrates consistent improvements, showcasing the potential of semantic graph smoothing in improving sentence embeddings for the supervised and unsupervised ...
Proposed Methodology: Smoothing Sentence Embeddings In this paper, we theorize that smoothing sentence embeddings with a semantic similarity graph can help supervised and unsupervised categorization models ...
arXiv:2402.12890v1
fatcat:kzqhngzgiva7bjnczi4uxmxxhy
A multispan language modeling framework for large vocabulary speech recognition
1998
IEEE Transactions on Speech and Audio Processing
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Since in this space familiar clustering techniques can be applied, it becomes possible to derive several families of large-span language models, with various smoothing properties. ...
This paradigm seeks to automatically uncover the salient semantic relationships between words and documents in a given corpus. ...
Landauer, from the same institution, for pointing out a number of insightful references on the latent semantic model of knowledge acquisition, and to the anonymous reviewers for their constructive comments ...
doi:10.1109/89.709671
fatcat:wkkgclrrinb7vjs7pw5aphrk3u
Investigating task performance of probabilistic topic models: an empirical study of PLSA and LDA
2010
Information retrieval (Boston)
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(LDA), using three representative text mining tasks, including document clustering, text categorization, and ad-hoc retrieval. ...
The task-based evaluation framework is generalizable to other topic models in the family of either PLSA or LDA. ...
Document clustering The first task we have chosen is document clustering. Generally, there are two ways of using topic models for document clustering. ...
doi:10.1007/s10791-010-9141-9
fatcat:v3vnphcmdrgblgziaudyddrtfu
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