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An evaluation of input data quality of lifelog analysis application with a framework based on quantitative index

Published: 20 February 2012 Publication History

Abstract

In recent years, by the improvement of the data acquisition technology and the development of storage, it has become greatly easier than before to collect lifelog that is to record the person's behavior as digital data. As a result, various lifelog analysis applications have been developed that offer the user profitable information such as person's action histories with an analysis of collected data by sensor terminals, video cameras, and so on.
However, in these lifelog analysis applications, the quality of the data that was collected from the sensor terminals and inputted to the application was not discussed in detail. Therefore, in this paper, we have focused on the quality of video image data and the acceleration data of objects. As a representative lifelog analysis application, we have chosen an application which verbalizes person's behavior from the data, and shown the influence of the quality of input data on the execution result of the application by a quantitative index.
An evaluation framework is proposed for the discussion of a correlation between input data and execution results of the application. As data processing methods, Bayesian Classifier and HMM are employed in his paper. With various conditions, it has been clarified how the quality of input data affects the result of the lifelog analysis application.

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  1. An evaluation of input data quality of lifelog analysis application with a framework based on quantitative index

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      cover image ACM Conferences
      ICUIMC '12: Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication
      February 2012
      852 pages
      ISBN:9781450311724
      DOI:10.1145/2184751
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 20 February 2012

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      Author Tags

      1. Bayesian classifier
      2. data quality
      3. hidden Markov model
      4. lifelog analysis
      5. quantitative index

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