Learn More
At our second participation in NTCIR RITE, we developed a twostage knowledge-based textual inference recognition system for both BC and MC subtasks in Chinese. Two main recognition systems, which are based on named entities, Chinese tokens, word dependency, and sentence length, were implemented to identify the entailment and contradiction between sentences.(More)
This work proposes a novel metric, Maximally Amortized Cost (MAC), for cost evaluations of error correction of predictive Chinese input methods (IMs). With a series of real-time simulation, user correction behaviors are analyzed by estimating generalized backward compatibility of adaptive Chinese IMs. Comparisons between three IMs by using MAC with(More)
We present a framework for identifying the most representative sentence patterns from semantically and syntactically-annotated corpora via a Semantic Frame Generation (SFG). One of the difficulties to find out similar concepts from a text is because of the variations in linguistic expressions. SFG uses linguistic units as backbones to generate the most(More)
We propose a statistical frame-based approach (FBA) for natural language processing, and demonstrate its advantage over traditional machine learning methods by using topic detection as a case study. FBA perceives and identifies semantic knowledge in a more general manner by collecting important linguistic patterns within documents through a unique flexible(More)
Apoptosis is a tightly controlled process in mammalian cells. It is important for embryogenesis, tissue homoeostasis, and cancer treatment. Apoptosis not only induces cell death, but also leads to the release of signals that promote rapid proliferation of surrounding cells through the Phoenix Rising (PR) pathway. To quantitatively understand the kinetics of(More)
  • 1