In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.

[Q]: Chinese word segmentation is a fundamental task for Chinese language processing. The granularity mismatch problem is the main cause of the errors. This paper showed that the binary tree representation can store outputs with different granularity. A binary tree based framework is also designed to overcome the granularity mismatch problem. There are two steps in this framework, namely tree building and tree pruning. The tree pruning step is specially designed to focus on the granularity problem. Previous work for Chinese word segmentation such as the sequence tagging can be easily employed in this framework. This framework can also provide quantitative error analysis methods. The experiments showed that after using a more sophisticated tree pruning function for a state-of-the-art conditional random field based baseline, the error reduction can be up to 20%.
[A]: Binary Tree based Chinese Word Segmentation


[Q]: We propose a framework grounded in Logic Programming for representing and reasoning about business processes from both the procedural and ontological point of views. In particular, our goal is threefold: (1) define a logical language and a formal semantics for process models enriched with ontology-based annotations; (2) provide an effective inference mechanism that supports the combination of reasoning services dealing with the structural definition of a process model, its behavior, and the domain knowledge related to the participating business entities; (3) implement such a theoretical framework into a process modeling and reasoning platform. To this end we define a process ontology coping with a relevant fragment of the popular BPMN modeling notation. The behavioral semantics of a process is defined as a state transition system by following an approach similar to the Fluent Calculus, and allows us to specify state change in terms of preconditions and effects of the enactment of activities. Then we show how the procedural process knowledge can be seamlessly integrated with the domain knowledge specified by using the OWL 2 RL rule-based ontology language. Our framework provides a wide range of reasoning services, including CTL model checking, which can be performed by using standard Logic Programming inference engines through a goal-oriented, efficient, sound and complete evaluation procedure. We also present a software environment implementing the proposed framework, and we report on an experimental evaluation of the system, whose results are encouraging and show the viability of the approach.
[A]: Ontology-based Representation and Reasoning on Process Models: A Logic Programming Approach


[Q]: A method is presented for the rhythmic pars­<lb>ing problem: Given a sequence of observed<lb>musical note onset times, we simultaneously<lb>estimate the corresponding notated rhythm<lb>and tempo process. A graphical model is<lb>developed that<lb>represents the evolution of<lb>tempo and rhythm and relates these hid­<lb>den quantities to an observable performance.<lb>The rhythm variables are discrete and the<lb>tempo and observation variables are contin­<lb>uous. We show how to compute the<lb>glob­<lb>ally most likely configuration of the tempo<lb>and rhythm variables given an observation of<lb>note onset times. Preliminary experiments<lb>are presented on a small data set. A gen­<lb>eralization to computing MAP estimates for<lb>arbitrary conditional Gaussian distributions<lb>is outlined.
[A]:
A Mixed Graphical Model for Rhythmic Parsing