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Co-occurrence-based analysis and synthesis of textures
Proceedings of 12th International Conference on Pattern Recognition, 2002In the first part of this paper, an algorithm for synthesizing textures obeying a given set of co-occurrence features is presented. It is shown that the synthetically generated images are visually very similar to remotely sensed images coming from the Landsat/TM and ERS1/AMI sensors.
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Temporal co-occurrence matrix approaches to motion analysis
SPIE Proceedings, 2004We propose a novel method for motion analysis in video sequences. It extends the co-occurrence matrix concept for texture analysis to the temporal domain. The approach proved to be versatile in the sense of targeting different motion analysis tasks.
A. Ukovich +2 more
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Identification and Analysis of Medical Entity Co-occurrences in Twitter
Proceedings of the ACM Ninth International Workshop on Data and Text Mining in Biomedical Informatics, 2015Twitter is an attractive source of data for public health surveillance, as it is less hindered by the legal and technical obstacles associated with data sources such as electronic health records. We present a preliminary co-occurrence analysis based on 10% of all tweets from 2014 annotated with medical entities as a first approach to extract health ...
Andrew MacKinlay +2 more
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A Note on the Analysis of Species Co‐Occurrences
Ecology, 1995The analysis of records of species occurrences on islands in an attempt to detect interactions between species has been an area of controversy in recent years in terms of the validity of some of the statistical methods used. In this note I make two contributions to the continuing debate.
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Conceptualization of place via spatial clustering and co-occurrence analysis
Proceedings of the 2009 International Workshop on Location Based Social Networks, 2009More and more users are contributing and sharing more and more contents on the Web via the use of content hosting sites and social media services. These user-generated contents are tagged with terms characterizing the contents from the users' perspectives.
Dong-Po Deng +2 more
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Event Recognition Based on Co-occurrence Concept Analysis
2013This paper proposes a kind of event recognition technique on news events which analyzes the words in the news documents using co-occurrence analysis for mining the key meta-event, and realizes more pervasive event recognition by leveraging on Markov chain. This approach overcomes the over-sensitivity problems in the traditional event recognition domain
Yi Zheng, Shi Ying, Yibing Wang
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Visual Analysis of Tag Co-occurrence on Nouns and Adjectives
2013In recent years, due to the wide spread of photo sharing Web sites such as Flickr and Picasa, we can put our own photos on the Web and show them to the public easily. To make the photos searched for easily, it is common to add several keywords which are called as “tags” when we upload photos. However, most of the tags are added one by one independently
Yuya Kohara, Keiji Yanai
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Term Co-occurrence Analysis as an Interface for Digital Libraries
2002We examine the relationship between term co-occurrence analysis and a user interface for digital libraries. We describe a current working implementation of a dynamic visual information retrieval system based on co-cited author maps that assists in browsing and retrieving records from a large-scale database, ten years of the Arts & Humanities Citation ...
Jan W. Buzydlowski +2 more
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A semantic model for flash retrieval using co-occurrence analysis
Proceedings of the eleventh ACM international conference on Multimedia, 2003Flash is experiencing a breathtaking growth and has become one of the prevailing media formats on the Web. Our goal is to exploit the enormous Flash resources by developing a model of content-based Flash retrieval. Towards this end, we introduce a novel approach for discovering semantic relationships among the co-occurrence patterns of elements in ...
Dawei Ding 0003 +3 more
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Co-occurrence-based texture analysis using irregular tessellations
Proceedings of 13th International Conference on Pattern Recognition, 1996Grey level co-occurrence features are one of the most powerful feature sets available for texture analysis. However, the moving window commonly employed to define the statistical scale at which the co-occurrence matrix is obtained assumes spatial stationarity of the underlying random field. This assumption is inappropriate in the case of natural images
Fernando Bello, Richard I. Kitney
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