Hiromi Narimatsu

Duration and Interval Hidden Markov Model for sequential data analysis

Analysis of sequential event data has been recognized as one of the essential tools in data modeling and analysis field. In this paper, after the examination of its technical requirements and issues to model complex but practical situation, we propose a new sequential data model, dubbed Duration and Interval Hidden Markov Model (DI-HMM), that efficiently represents “state duration” and “state interval” of data events. This has significant implications to play an important role in representing practical time-series sequential data. This eventually provides an efficient and flexible sequential data retrieval. Numerical experiments on synthetic and real data demonstrate the efficiency and accuracy of the proposed DI-HMM.

Efficient resource access algorithm for context-aware user assist services on portable devices

With the promising user assist services on portable devices, service controllers in multiple applications must continuously monitor dynamically changeable data and status, and judge whether its service action should be activated. These operations in a real-time manner bring heavy resource consumption on the portable devices. This paper proposes an innovative way to reduce the consumption by aggregating resource accesses timings requested from multiple applications. The simulation shows that the proposed method can provide the highest precision information while keeping the resource consumption lower.

Selective Data Deactivation Mechanism in Sustainable Area-based Cache for Mobile Social Networks

This paper presents a proposal of a more resilient mechanism of an area-based sustainable cache system under a temporary decrease of the number of terminals. This mechanism suppresses interruptions of data relay and disappearances of cache data in the cache continually. The core technology enables each terminal to retain the received data in cache areas as “deactivated data” instead of deleting the data, even after a terminal leaves the area. Deactivated data are not relayed outside the target designated cache area. The data are reactivated and redistributed to others as relay data once the terminal revisits there. Consequently, the data are shared across time. Furthermore, particularly addressing the limitation of terminal storage, we proposed an adaptive scheme to select which data should be retained as deactivation data. This new mechanism leverages the proposed method under the storage limitation. As presented at the end of this paper, the simulation evaluations underscore the effectiveness of the proposed mechanism, and the adaptive selective scheme of deactivated data.

Data access aggregation for context-aware services on CE portable devices

With the promising development of user assist services on consumer electronics portable devices, service applications must continuously monitor dynamically changeable data and status, and judge whether their service actions should be activated. These operations, performed in real-time, result in heavy resource consumption on the portable devices. This paper proposes an innovative way to reduce the consumption by aggregating data access timings requested from multiple applications. Simulation shows that the proposed method can provide the highest precision data while reducing resource consumption. This mechanism can be installed into an operation system on a mobile device, or can operate as a middleware on the device. This must be one of key technologies to reduce battery power consumption of CE devices.

A classifier-based approach to supporting the augmentation of the question-answer database for spoken dialogue systems

Dealing with a variety of user questions in question-answer spoken dialogue systems requires preparing as many question-answer patterns as possible. This paper proposes a method for supporting the augmentation of the question-answer database. It uses user questions collected with an initial question-answer system, and detects questions that need to be added to the database. It uses two language models; one is built from the database and the other is a large-vocabulary domain-independent model. Experimental results suggest the proposed method is effective in reducing the amount of effort for augmenting the database when compared to a baseline method that used only the initial database.

State duration and interval modeling in hidden semi-Markov model for sequential data analysis

Sequential data modeling and analysis have become indispensable tools for analyzing sequential data, such as time-series data, because larger amounts of sensed event data have become available. These methods capture the sequential structure of data of interest, such as input-output relations and correlation among datasets. However, because most studies in this area are specialized or limited to their respective applications, rigorous requirement analysis of such models has not been undertaken from a general perspective. Therefore, we particularly examine the structure of sequential data, and extract the necessity of “state duration” and “state interval” of events for efficient and rich representation of sequential data. Specifically addressing the hidden semi-Markov model (HSMM) that represents such state duration inside a model, we attempt to add representational capability of a state interval of events onto HSMM. To this end, we propose two extended models: an interval state hidden semi-Markov model (IS-HSMM) to express the length of a state interval with a special state node designated as “interval state node”; and an interval length probability hidden semi-Markov model (ILP-HSMM) which represents the length of the state interval with a new probabilistic parameter “interval length probability.” Exhaustive simulations have revealed superior performance of the proposed models in comparison with HSMM. These proposed models are the first reported extensions of HMM to support state interval representation as well as state duration representation.

Resource access aggregation for mobile CE device

This paper proposes an innovative way to reduce the consumption by aggregating resource accesses timings requested from multiple applications. The simulation shows that the proposed method can provide the highest precision information while keeping the resource consumption lower.

Location-based distributed mobile storage using short-range wireless communication

This paper proposes a new distributed mobile storage architecture to store information in a local area by collaborating end-terminals without an infrastructure network. This paper shows the effectiveness of the proposed control algorithm by the simulation experiment.