Gaussian Overlapping and the Jaccard Similarity Coefficient
Unilateral Jaccard Similarity Coefficient
... 2. PARADIGMATIC SIMILARITY DEFINI- TION 2.1 Basics Of Paradigmatic Structures Paradigmatic analysis is a process that identifies entities which are not related directly but are related by their prop- erties, ...
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Using of Jaccard Coefficient for Keywords Similarity
... a similarity measurement between keywords and index terms is essentially performed to facilitate searchers in accessing the required results ...the similarity measurement method between words by deploying ...
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SparseHash: Embedding Jaccard coefficient between supports of signals
... a similarity in- dex between sets, where the elements in the sets are the vo- cabulary elements present in the objects under ...the Jaccard similarity coeffi- cient between pairs of sets and is used ...
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Keywords Data Cleaning, De-Duplication, Jaccard Method of similarity.
... The original and duplicate data are being differentiated using Jaccard coefficient method on the dataset. And the generalized method used to compare data is also efficient. This method takes less time. Data ...
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Online Service Rating Prediction by Removing Paid Users and Jaccard Coefficient
... Jaccard Coefficient In this technique let the two user are present in the social network, then find number of common friends between those ...is Jaccard coeffiecient. As value of this ...
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Detection Coronavirus using Cased-Based Reasoning with Extended Jaccard Coefficient
... Extended Jaccard Coefficient ...Extended Jaccard Coefficient method can model the level of similarity of a new case to an old ...
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An Improvement of Plagiarized Area Detection System Using Jaccard Correlation Coefficient Distance Algorithm
... higher similarity value of 63% the target document should be passed to check whether the target document is plagiarized or ...the similarity between two example documents is 17%, the target document is not ...
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Detecting Overlapping Community in Complex Network Based on Node Similarity
... calculates similarity between two nodes in the network by means of Jaccard similarity measure ...the similarity value, combining with the community according to the change of ...the ...
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Novel similarity measure for interval valued data based on overlapping ratio
... the similarity of intervals, current similarity measures such as the commonly used Jaccard and Dice measures are at times not sensitive to changes in the width of intervals, producing equal ...
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Novel similarity measure for interval-valued data based on overlapping ratio
... the similarity of intervals, current similarity measures such as the commonly used Jaccard and Dice measures are at times not sensitive to changes in the width of intervals, producing equal ...
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Performance Analysis of Similarity Coefficient Feature Vector on Facial Expression Recognition
... New similarity based feature vector is applied on which the histogram for all features vector in each block is connected to form the global feature vector for the whole ...new Jaccard similarity ...
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Similarity Coefficient Measures Applied to Integrate Feasibility Assessment and the Design of Cellular Manufacturing Systems
... Methodology: This study followed the same procedures of Basher and Karaa in 2008 that used for predicting the machine cells number in FA in all the three proposed methods. However, Basher and Karaa used Jaccard in ...
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A Performance Evaluation of SMCA Using Similarity Association & Proximity Coefficient Relation For Hierarchical Clustering
... Density-based methods assume that the points that belong to each cluster are drawn from a specific probability distribution (Banfield and Raftery, 1993).The overall distribution of the data is assumed to be a mixture of ...
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Text Independent Automatic Speaker Recognition System Using Mel Frequency Cepstrum Coefficient and Gaussian Mixture Models
... the similarity estimation of each test with respect to each profile stored in the sys- ...the similarity likelihood of test speaker i with respect to training speaker ...
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On the Jaccard Index Similarity Measure in Ranking Fuzzy Numbers
... the similarity measure technique. Jaccard index similarity measure has been introduced in ranking the fuzzy numbers where fuzzy maximum, fuzzy minimum, fuzzy evidence and fuzzy total evidence are ...
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Selecting image pairs for SfM by introducing Jaccard Similarity
... Some SfM methods detect candidate image pairs beforehand in order to avoid exhaustive matching. Match- Miner [11] is one of the methods used for selecting image pairs. It adopts the bag-of-visual-words and tf-idf weight- ...
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Forecasting Model Based on Neutrosophic Logical Relationship and Jaccard Similarity
... the Jaccard similarity measure, and on fluctuations of the time ...the Jaccard similarity measure method to find the optimal forecasting ...
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Comparison Jaccard similarity, Cosine Similarity and Combined Both of the Data Clustering With Shared Nearest Neighbor Method
... value similarity. Jaccard similarity method used similarity, cosine similarity and a combination of Jaccard similarity and cosine ...two similarity is expected to ...
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A query suggestion method combining TF-IDF and Jaccard Coefficient for interactive web search
... This paper proposes a query suggestion method combining two ranked retrieval methods: TF-IDF and Jaccard coefficient. Four performance criteria plus user evaluation have been adopted to evaluate this ...
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Overlapping Mixtures of Gaussian Processes for the data association problem
... nentially. Some attempts have been made to restrain this combinatorial explosion, including the heuristic methods from [ 10 , 11 ]. In this paper we present an algorithm based on Gaussian Processes that is able ...
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