• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.4
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• pp.259-262
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• 2010

Study about fuzzy entropy and similarity measure on intuitionistic fuzzy sets (IFSs) were proposed, and analyzed. Unlike fuzzy set, IFSs contains uncertainty named hesistancy, which is contained in fuzzy membership function itself. Hence, designing fuzzy entropy is not easy because of ununified entropy definition. By considering different fuzzy entropy definitions, fuzzy entropy is designed and discussed their relation. Similarity measure was also presented and verified its usefulness to evaluate degree of similarity.

• Language and Information
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• v.14 no.1
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• pp.113-144
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• 2010

The primary goal of this paper is to find a feasible way to answer the question: Does the similarity in meaning between verbs relate to the similarity in their subcategorization? In order to answer this question in a rather concrete way on the basis of a large set of English verbs, this study made use of various language resources, tools, and statistical methodologies. We first compiled a list of 678 verbs that were selected from the most and second most frequent word lists from the Colins Cobuild English Dictionary, which also appeared in WordNet 3.0. We calculated similarity measures between all the pairs of the words based on the 'jcn' algorithm (Jiang and Conrath, 1997) implemented in the WordNet::Similarity module (Pedersen, Patwardhan, and Michelizzi, 2004). The clustering process followed, first building similarity matrices out of the similarity measure values, next drawing dendrograms on the basis of the matricies, then finally getting 177 meaningful clusters (covering 437 verbs) that passed a certain level set by z-score. The subcategorization frames and their frequency values were taken from the ICE-GB. In order to calculate the Selectional Preference Strength (SPS) of the relationship between a verb and its subcategorizations, we relied on the Kullback-Leibler Divergence model (Resnik, 1996). The SPS values of the verbs in the same cluster were compared with each other, which served to give the statistical values that indicate how much the SPS values overlap between the subcategorization frames of the verbs. Our final analysis shows that the degree of overlap, or the relationship between semantic similarity and the subcategorization frames of the verbs in English, is equally spread out from the 'very strongly related' to the 'very weakly related'. Some semantically similar verbs share a lot in terms of their subcategorization frames, and some others indicate an average degree of strength in the relationship, while the others, though still semantically similar, tend to share little in their subcategorization frames.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.441-443
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• 2021

Sentence or text similarity is a measure of the degree of similarity between two sentences. Techniques for measuring text similarity include Jacquard similarity, cosine similarity, Euclidean similarity, and Manhattan similarity. Currently, the cosine similarity technique is most often used, but since this is an analysis according to the occurrence or frequency of a word in a sentence, the analysis on the semantic relationship is insufficient. Therefore, we try to improve the efficiency of analysis on the similarity of sentences by giving relations between words using ontology and including semantic similarity when extracting words that are commonly included in two sentences.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.14-25
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• 2020

This research proposes a methodology to evaluate the rationality of passengers' route choice who make trips within Seoul metropolitan subway based on smart card data. The rationality of user route choice is divided into the degree of determinacy and similarity concepts as basic principle. Determinacy is the degree to which the route selected by the passenger is identical to the system optimal path. Similarity indicates the degree to which the route is similar to the system optimal path. The K-path search method is used for path enumeration, which allows for measurement of determinacy. To assess determinacy within similarity, transfer tag data of private operators is used. Consequently, the concept of similarity applied to the model is such that the passenger's path choice is identical to the path taken using the tag reader. Results show that the determinacy of appearance of the shortest path (K=1) is 90.4%, while the similarity of appearance as K=(2-10) is 7.9%, summing to 98.3%. This indicates that trips on the metropolitan subway network are being rationally explained. 1.7% of irrational trips are attributed to the unexplainable error term that occurs due to the diversity of passengers.

• The KIPS Transactions:PartA
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• v.15A no.2
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• pp.125-134
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• 2008

We implemented a system being able to suggest example sentences for multiple choice tests, considering the level of students. To build the system, we designed an automatic method for sentence generation, which made it possible to control the difficulty degree of questions. For the proper evaluation in the multiple choice tests, proper size of question pools is required. To satisfy this requirement, a system which can generate various and numerous questions and their example sentences in a fast way should be used. In this paper, we designed an automatic generation method using a linguistic resource called WordNet. For the automatic generation, firstly, we extracted keywords from the existing sentences with the morphological analysis and candidate terms with similar meaning to the keywords in Korean WordNet space are suggested. When suggesting candidate terms, we transformed the existing Korean WordNet scheme into a new scheme to construct the concept similarity matrix. The similarity degree between concepts can be ranged from 0, representing synonyms relationships, to 9, representing non-connected relationships. By using the degree, we can control the difficulty degree of newly generated questions. We used two methods for evaluating semantic similarity between two concepts. The first one is considering only the distance between two concepts and the second one additionally considers positions of two concepts in the Korean Wordnet space. With these methods, we can build a system which can help the instructors generate new questions and their example sentences with various contents and difficulty degree from existing sentences more easily.

• Korean Institute of Interior Design Journal
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• v.24 no.2
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• pp.32-41
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• 2015

We live in the era of unlimited design competition. As the importance of design is increasing in all areas including marketing, each country does its best effort on design development. However, the preparation on protecting interior design rights by intellectual property laws(IPLs) has not been enough even though they occupy an important place in the design field. It is not quite easy to make a judgement on the similarity between two images having a single common factor because the factors which are composed of interior design have complicated interactive relations between them. From the IPLs point of view, designs with the similar overall appearance are decided to be similar. Objective evaluation criteria not only for designers but also for design examiners and judges are required in order to protect interior design by the IPLs. The objective of this study is the analysis of the possibility that a computer algorithm method can be useful to decide the similarity of interior design images. According to this study, it is realized that the Img2 which is one of content-based image retrieval computer programs can be utilized to measure the degree of the similarity. The simulation results of three descriptors(CEDD, FCTH, JCD) in the Img2 showed the high degree of similar patterns compared with the results of perceptual judgment by observers. In particular, it was verified that the Img2 has high availability on interior design images with a high score of similarity below 60 which are perceptually judged by observers.

• Journal of KIISE:Databases
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• v.34 no.5
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• pp.437-447
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• 2007

A variety of similarity metrics have been used to measure the degree of web page changes. In this paper, we first define criteria for web page changes to evaluate the effectiveness of the similarity metrics in terms of six important types of web page changes. Second, we propose a new similarity metric appropriate for measuring the degree of web page changes. Using real web pages and synthesized pages, we analyze the five existing metrics (i.e., the byte-wise comparison, the TF IDF cosine distance, the word distance, the edit distance, and the shingling) and ours under the proposed criteria. The analysis result shows that our metric represents the changes more effectively than other metrics. We expect that our study can help users select an appropriate metric for particular web applications.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1565-1568
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• 1997

In this paper, a fuzzy based machine-cell formation algorithm for cellular manufacturing is presented. The fuzzy lovic is employed to express the degree of appropriateness when alternative machnies are specified to process a part shape. For machine grouping, the similarity coefficient based approach is used. The algorithm produces efficient machine cells and part families which maximize the similarity values.

• Journal of Information Science Theory and Practice
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• v.7 no.3
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• pp.31-39
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• 2019

Nowadays, recommender systems suggest lists of items to users considering not only accuracy but also diversity and novelty. However, suggesting the most diverse list of items to all users is not always acceptable, since different users prefer and/or tolerate different degree of diversity. Hence suggesting a personalized list with a diversity degree considering each user preference would improve the efficiency of recommender systems. The main contribution and novelty of this study is to tune the diversity degree of the recommendation list based on the users' variety-seeking feature, which ultimately leads to users' satisfaction. The proposed approach considers the similarity of users' desire diversity as a new parameter in addition to the usual similarity of users in the state-of-the-art collaborative filtering algorithm. Experimental results show that the proposed approach improves the personal diversity criterion comparing to the closest method in the literature, without decreasing accuracy.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.81-86
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• 2001

In this paper, we investigated the modeling of Bank Asset Management System(BAME) based on intelligent agent. To achieve this goal, we introduced several kinds of agents that show intelligent features. BAMS is a user friendly system and adopts fuzzy converting system and fuzzy matching system that returns reasonable similarity matching results. Generation function of the proximity degree is suggested. Fuzzification of investment type categories and feature values are defined, and generation of proximity degree is also derived. An example of bank asset management system is introduced and simulated. Investment type matching utilizing fuzzy measure is tested and it showed quite reasonable similarity matching results.