20,364 research outputs found
An Open Source Testing Tool for Evaluating Handwriting Input Methods
This paper presents an open source tool for testing the recognition accuracy
of Chinese handwriting input methods. The tool consists of two modules, namely
the PC and Android mobile client. The PC client reads handwritten samples in
the computer, and transfers them individually to the Android client in
accordance with the socket communication protocol. After the Android client
receives the data, it simulates the handwriting on screen of client device, and
triggers the corresponding handwriting recognition method. The recognition
accuracy is recorded by the Android client. We present the design principles
and describe the implementation of the test platform. We construct several test
datasets for evaluating different handwriting recognition systems, and conduct
an objective and comprehensive test using six Chinese handwriting input methods
with five datasets. The test results for the recognition accuracy are then
compared and analyzed.Comment: 5 pages, 3 figures, 11 tables. Accepted to appear at ICDAR 201
Personalized Fuzzy Text Search Using Interest Prediction and Word Vectorization
In this paper we study the personalized text search problem. The keyword
based search method in conventional algorithms has a low efficiency in
understanding users' intention since the semantic meaning, user profile, user
interests are not always considered. Firstly, we propose a novel text search
algorithm using a inverse filtering mechanism that is very efficient for label
based item search. Secondly, we adopt the Bayesian network to implement the
user interest prediction for an improved personalized search. According to user
input, it searches the related items using keyword information, predicted user
interest. Thirdly, the word vectorization is used to discover potential targets
according to the semantic meaning. Experimental results show that the proposed
search engine has an improved efficiency and accuracy and it can operate on
embedded devices with very limited computational resources
Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure
Big data research has attracted great attention in science, technology,
industry and society. It is developing with the evolving scientific paradigm,
the fourth industrial revolution, and the transformational innovation of
technologies. However, its nature and fundamental challenge have not been
recognized, and its own methodology has not been formed. This paper explores
and answers the following questions: What is big data? What are the basic
methods for representing, managing and analyzing big data? What is the
relationship between big data and knowledge? Can we find a mapping from big
data into knowledge space? What kind of infrastructure is required to support
not only big data management and analysis but also knowledge discovery, sharing
and management? What is the relationship between big data and science paradigm?
What is the nature and fundamental challenge of big data computing? A
multi-dimensional perspective is presented toward a methodology of big data
computing.Comment: 59 page
- …