unsupervised approach
Unsupervised Approach for Dialogue Act Classification
... There are several unsupervised clustering methods. We used the K-means clustering algorithm (e.g., (Duda et al., 2000)) that is very simple because, at the moment, a highly sophisticated method in which analyzing ...
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Unsupervised Approach for Retrieving Shots from Video
... an unsupervised approach for retrieving required video ...The approach begins with identify- ing shots, followed by indexing the shots for ...
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A New Unsupervised Approach to Word Segmentation
... This article proposes ESA, a new unsupervised approach to word segmentation. ESA is an iterative process consisting of three phases: Evaluation, Selection, and Adjustment. In Eval- uation, both the ...
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An Unsupervised Approach for Semantic Relation Interpretation
... In this paper we have introduced a hybrid unsupervised approach for semantic relation extraction from Italian and English texts. The implemented system, called RelEx, takes as input pairs of ...
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An Unsupervised Approach to Biography Production Using Wikipedia
... our approach has the following advantages: It employs no manual annotation but relies upon identifying appropriately different corpora to represent our training ...
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Bootstrapping an Unsupervised Approach for Classifying Agreement and Disagreement
... Their approach achieved an accuracy of ...Their approach reached an accuracy of 73% and thus outperforms Naïve Bayes classifiers which usually achieve accuracies of 58-64% in the same ...
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An Unsupervised Approach to Recognizing Discourse Relations
... In order to collect training cases, we mined in an unsupervised manner two corpora. The first corpus, which we call Raw, is a corpus of 1 billion words of unannotated English (41,147,805 sentences) that we created ...
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Detecting Derogatory Compounds – An Unsupervised Approach
... We present the first study to detect derogatory noun-noun compounds and propose an unsuper- vised classification approach based on distribu- tional information that does not require any prop- erly labeled training ...
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Identifying value mappings for data integration: An unsupervised approach
... Simple Vector Model. Consider tables in Table 1. Suppose we want to find the value mapping between terms used in three columns, Gender, T itle, and Degree across the two tables. One simple solution is to use frequencies ...
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The FLORES Evaluation Datasets for Low Resource Machine Translation: Nepali–English and Sinhala–English
... an unsupervised way with English, Hindi and Nepali monolingual data using the unsupervised approach by Lample and Con- neau (2019), and it is then jointly trained on both the Nepali–English ...
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Finding Recurrent Patterns from Continuous Sign Language Sentences for Automated Extraction of Signs
... an unsupervised approach to automatically extract parts of signs that are robust to the variation of adjacent signs si- multaneously from multiple sign language sentences, (ii) our approach does not ...
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Taxonomy Learning to Improve Overall Associative Strength among Concept-A Graph Based Approach
... based approach unsupervised approach named as taxofinder for taxonomy learning that automatically builds a taxonomy from semantic graph named cgraph of concepts modeled from target ...
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Mapping semantic knowledge for unsupervised text categorisation
... Unsupervised text categorisation classifies documents into categories with absence of any pre-labelled sam- ples for training. Without labelled samples, Yang et al. (Yang et al. 2010) have formalised a categorisa- ...
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Identifying aggressive prostate cancer foci using a DNA methylation classifier
... While clinical tools and techniques have improved immensely [1, 3, 38–41], the determination of tumor ag- gressiveness prior to physical manifestation must rely on biomarkers measured biochemically or at a molecular ...
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Influence over the Dimensionality Reduction and Clustering for Air Quality Measurements using PCA and SOM
... This paper focuses on multivariate statistical and artificial neural networks techniques for data reduction. Each method has a different rationale to preserve the relationship between input parameters during analysis. ...
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Vol 9, No 9 (2019)
... Experimental results demonstrate blocking classifier were able to limit the number of record comparisons that take place thereby improving accuracy. 58 This was done by effectively grouping source data using similarity ...
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Validation of hierarchical gene clusters using repeated measurements
... There are few papers which utilized stability or bootstrap to deal with the optimal number of clusters. A resampling-based prediction method to estimate the number of clusters was proposed by Dudoit and Fridlyand [3], ...
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A Bootstrapping Approach to Unsupervised Detection of Cue Phrase Variants
... We demonstrate that such an approach is more appropriate for our task than IE/QA bootstrapping mechanisms based on cue phrase-external con- text. Part of the reason for why normal boot- strapping does not work for ...
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Catchment based gold prospectivity analysis combining geochemical, geophysical and geological data across northern Australia
... The curse of dimensionality describes the increase in the distance between samples as the number of features increases. Hence, a focus of further research should investigate dimension- ality reduction approaches such as ...
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COMPARATIVE ANALYSIS OF MACHINE LEARNING AND LEXICON BASED TECHNIQUE IN ENHANCING THE EFFICACY OF ‘SENTIMENT ANALYSIS’
... half approach utilizing a dictionary/learning beneficial interaction is to locate the best of together universes security just as coherence from a painstakingly arranged vocabulary, and the high precision from an ...
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