Textual entailment is knowledge that may prove useful for a variety of applications dealing with inferencing over sentences described in natural language texts. This paper proposes a method to calculate the similarity between two text fragments T and H which is based on the TF-IDF algorithm. Similarity calculation, which contains synonymous degree and particular degree, is an important part in ...

In Programming by Example, a system attempts to infer a program from input and output examples, generally by searching for a composition of certain base functions. Performing a naı̈ve brute force search is infeasible for even mildly involved tasks. We note that the examples themselves often present clues as to which functions to compose, and how to rank the resulting programs. In text processing...

Many current documents include multimedia consisting of text, images and embedded videos. This paper presents a general method that uses Random Forests to automatically extract keyphrases that can be used as very short summaries and to help in retrieval, classification and clustering processes.

We present two regression models for the prediction of pairwise preference judgments among MT hypotheses. Both models are based on feature sets that are motivated by textual entailment and incorporate lexical similarity as well as local syntactic features and specific semantic phenomena. One model predicts absolute scores; the other one direct pairwise judgments. We find that both models are co...

We address class imbalance problems. These are classification problems where the target variable is binary, and one dominates over other. A central objective in these to identify features that yield models with high precision/recall values, standard yardsticks for assessing such models. Our extracted from textual data inherent use n-gram frequencies as introduce a discrepancy score measures eff...

Textual CBR systems solve problems by reusing experiences that are in textual form. Knowledge-rich comparison of textual cases remains an important challenge for these systems. However mapping text data into a structured case representation requires a significant knowledge engineering effort. In this paper we look at automated acquisition of the case indexing vocabulary as a two step process in...