{"title":"A Japanese Language Model with Quote Detection by Using Surface Information","authors":"M. M. González, H. Nomura","doi":"10.1109/MICAI.2008.30","DOIUrl":"https://doi.org/10.1109/MICAI.2008.30","url":null,"abstract":"In natural language processing, quotes are an important grammatical category which needs consideration. In this paper, we propose a Japanese language model that includes quotes as a category. The quotes are recognized by using surface information and dependencies between the words. Then, they are divided into direct and indirect speech. Finally, we extract the quotes and create a relation between them and the original text. After the text has been analyzed, we obtain a tree structure with all the elements hierarchically categorized. We have experimentally tested the accuracy of the parsing process by creating a prototype system. The results show a 67.29% overall correct quote detection.","PeriodicalId":301028,"journal":{"name":"2008 Seventh Mexican International Conference on Artificial Intelligence","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121064278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Facilitating Access Control at Groupwork by Means of an Ontology of Its Organizational Structure and Concept of Stage","authors":"M. Anzures-García, L. A. Sánchez-Gálvez","doi":"10.1109/MICAI.2008.66","DOIUrl":"https://doi.org/10.1109/MICAI.2008.66","url":null,"abstract":"In the groupware applications one of the principal aims is to supply a common context, so the more information gets shared, the more easily common context can be achieved. However, the sharing of information in this type of applications leads to provide security mechanisms. Controlling the access to resources and activities is a key element in system security. In this paper, we focus in access control mechanism for security management. For this reason, firstly, we use a methodology to model the policy-based groupwork organizational structure management, which enables at system uses concepts to describe organization of the groupwork. The policy establishes the access control to the shared resources, since defines an organizational structure by means of the roles that users can play. Secondly, we consider that groupware applications contain several stages, for example, a conference management system has stages: submission, assignment, review, and acceptance of papers. At each stage role or roles that can participate are defined, in this way, we control access to shared workspace. Finally, we present an example to show as the methodology and concept of stages that we have used facilitate the access control in the groupware applications.","PeriodicalId":301028,"journal":{"name":"2008 Seventh Mexican International Conference on Artificial Intelligence","volume":"110 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121003372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Combining Genetic Algorithms and FLDR for Real-Time Voice Command Recognition","authors":"J. Romo, F. Rosas, M. Mora-González","doi":"10.1109/MICAI.2008.61","DOIUrl":"https://doi.org/10.1109/MICAI.2008.61","url":null,"abstract":"In this article we propose an effective method for a user-dependant voice command (small vocabulary) recognition system based on the combination of genetic algorithms and the Fisherpsilas linear discriminant ratio (FLDR). A genetic algorithm here is used to search in the frequency domain of the voice for those sub-bands whose energy is discriminant enough so as to distinguish between at least two different classes, and at the same time, being able to appropriately agglomerate the different utterances of one word of the vocabulary in a compact class. Once the sub-bands have been evolutionary selected, its energy is represented in feature vectors; in this way, very few samples of each voice command are required to build each word's model; moreover, this is a convenient method for feature selection. Real time implementation was done in a DSP TMS320LF2407 using elliptic bandpass filters -- one per sub-band -- with floating point representation. Encouraging results were obtained.","PeriodicalId":301028,"journal":{"name":"2008 Seventh Mexican International Conference on Artificial Intelligence","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128031066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Genetic Support Vector Classification and Feature Selection","authors":"Iván Mejía-Guevara, Ángel Kuri-Morales","doi":"10.1109/MICAI.2008.48","DOIUrl":"https://doi.org/10.1109/MICAI.2008.48","url":null,"abstract":"An important issue regarding the design of support vector machines (SVMs) is considered in this article, namely, the fine tuning of parameters in SVMs. This problem is tackled by using a self-adaptive genetic algorithm (GA). The same GA is used for feature selection. We validate our results implementing some statistical tests based on single domain benchmark data sets, which are used for comparison with other traditional methods. One of these methods is commonly used for the selection of parameters in SVMs.","PeriodicalId":301028,"journal":{"name":"2008 Seventh Mexican International Conference on Artificial Intelligence","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133953634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Color Morphological Image Segmentation on a New Opponent Color Space Based on the Notion of Critical Functions","authors":"Israel Santillan, Gilberto Herrera-Ruiz","doi":"10.1109/MICAI.2008.23","DOIUrl":"https://doi.org/10.1109/MICAI.2008.23","url":null,"abstract":"In the present paper color image segmentation, based on the notion of critical functions, is investigated. The notion of critical functions is derived from the well-known waterfall transformation. In the one-dimensional case the critical functions and the waterfall transformation provide similar results. However, in the two-dimensional case, the critical functions give better results for segmenting images than the waterfall transformation, since they take into account the fusion of regional minima (or maxima) to transform the image, providing a good control of the regions merging process. Moreover, contrary to the waterfall transformation which is non-parametric, critical functions allow the introduction of image segmentation criteria to compute an optimal partition. To carry out our study, a color space based on the opponent colors is proposed that we call YO1O2 model. The main reason to propose a new color space is that despite the numerous perceptually color spaces (HSV,HSL, HSI, among others) proposed in the literature, they have several drawbacks for color image processing. The performance in image segmentation of both proposals, the color model and critical functions, is illustrated with several examples. Also, some interesting properties of the color model YO1O2 and the critical functions are shown.","PeriodicalId":301028,"journal":{"name":"2008 Seventh Mexican International Conference on Artificial Intelligence","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125213567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Syntactico-Semantic Analysis: A Hybrid Sentence Extraction Strategy for Automatic Summarization","authors":"J. G. Flores, G. de Chalendar","doi":"10.1109/MICAI.2008.36","DOIUrl":"https://doi.org/10.1109/MICAI.2008.36","url":null,"abstract":"Automatic summarization systems often make use of sentence extraction methods to select significant content in texts. This paper presents two-sentence extraction strategies. The first one is based on a semantic analysis using word senses built by means of a network of lexical co-occurrences. The second one uses a combination of semantic and syntactical analysis to extract a set of relevant sentences. Both strategies are evaluated against a large corpus of newspaper and scientific articles, and their results are compared to Mead, a reference summarization tool. Evaluations results suggest that, inside the extractive summarization framework, the proposed hybrid strategy improves the relevance of the resulting summaries.","PeriodicalId":301028,"journal":{"name":"2008 Seventh Mexican International Conference on Artificial Intelligence","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122425407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Classification of Data Sequences by Similarity Analysis of Recurrence Plot Patterns","authors":"E. Bautista-Thompson, R. Brito-Guevara","doi":"10.1109/MICAI.2008.16","DOIUrl":"https://doi.org/10.1109/MICAI.2008.16","url":null,"abstract":"Quantification of the similarity between data sequences is important in different database and data mining tasks such as indexing, retrieving, clustering and classification, many similarity metrics (Euclidean, DTW, among others) operate directly in the raw representation of the sequences, but this implies when the sequences are compared, not take into account information about the collective behavior of the data that forms a sequence and the hidden relations between such data, such information can be important for classification of sequences based on their structures and their relations with the dynamics that such structures can represent (e.g. stationary, random, complex). We propose a computational technique for similarity analysis and classification of recurrence plot patterns: RecurrenceVs. The results show that the proposed technique is able to classify data sequences by similarity families based on the recurrence plot patterns, which preserve the information about the structure and dynamics represented by the data sequences.","PeriodicalId":301028,"journal":{"name":"2008 Seventh Mexican International Conference on Artificial Intelligence","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124624049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Classic Chinese Automatic Question Answering System Based on Pragmatics Information","authors":"Ye Yang, P. Jiang, F. Ren, S. Tsuchiya","doi":"10.1109/MICAI.2008.31","DOIUrl":"https://doi.org/10.1109/MICAI.2008.31","url":null,"abstract":"In this paper, we propose a practical question answering system for the \"Analects of Confucius\" based on the pragmatics information. The \"Analects of Confucius\" is a classic Chinese literature by the Confucian during the Warring States Period (476 B.C-221 B.C ). But the literature can not be categorized by topics and it has comprehensive meanings, not only the literal meanings and explicitly communicated meanings of the passages, but also deeper meanings and implicitly communicated meanings (Here, we call the deep meaning and implicitly communicated meaning as pragmatics information). Therefore we constructed a QA system, which aims to help understanding the ''Analects of Confucius'' correctly. According to the experiments, the pragmatics information based retrieval results are more accurate than the results based on the interpretations in modern language.","PeriodicalId":301028,"journal":{"name":"2008 Seventh Mexican International Conference on Artificial Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122688100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Gómez-Gil, M. Ramirez-Cortes, J. González-Bernal, Á. Pedrero, C. Prieto-Castro, D. Valencia, R. Lobato, J. E. Alonso
{"title":"A Feature Extraction Method Based on Morphological Operators for Automatic Classification of Leukocytes","authors":"P. Gómez-Gil, M. Ramirez-Cortes, J. González-Bernal, Á. Pedrero, C. Prieto-Castro, D. Valencia, R. Lobato, J. E. Alonso","doi":"10.1109/MICAI.2008.41","DOIUrl":"https://doi.org/10.1109/MICAI.2008.41","url":null,"abstract":"In this paper we present preliminary results obtained from the application of morphological operator pecstrum, for the extraction of discriminating characteristics in leukocytes and similar artificial images. Experts have identified six categories of leukocytes, very similar in shape and size, which makes them extremely difficult to distinguish automatically or even by non-expert humans. A feature vector based on a 7-component pecstrum, normalized area, and nucleus-cytoplasm area ratio, was tested using 4 kinds of recognizers: Euclidean distance, k-nearest neighbor, back propagation neural net and support vector machine. Using 36 patterns for training and 18 for testing, recognition of 87% was obtained in the best case, which is encouraging, given the complexity of the problem. The amount of samples used at this point for experiments is not statistically representative, however these results are promising and more experiments will be carried out.","PeriodicalId":301028,"journal":{"name":"2008 Seventh Mexican International Conference on Artificial Intelligence","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128647828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Cascading Decomposition and State Abstractions for Reinforcement Learning","authors":"C. Chiu, V. Soo","doi":"10.1109/MICAI.2008.65","DOIUrl":"https://doi.org/10.1109/MICAI.2008.65","url":null,"abstract":"Problem decomposition and state abstractions applied in the hierarchical problem solving often requires manual construction of a hierarchy structure in advance. This work is to provide some automatic algorithms for dimension reduction in problem solving. We propose cascading decomposition algorithm based on the spectral analysis on a normalized graph Laplacian to decompose the problem into several sub-problems and conduct parameter relevance analysis on each sub-problem to perform dynamic state abstraction. In each decomposed sub-problem, only parameters in the projected state space related to its sub-goal are reserved, and identical sub-problems are integrated into one through feature comparison. The whole problem is transformed into a combination of projected sub-problems, and problem solving in the abstracted space is more efficient. The paper demonstrates the performance improvement on reinforcement learning based on the proposed state space decomposition and abstraction methods using a capture-the-flag scenario.","PeriodicalId":301028,"journal":{"name":"2008 Seventh Mexican International Conference on Artificial Intelligence","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115422327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}