Assessing Natural Language: Measuring Emotion-Words within a Sentence or Without a Sentence?

Within and across sentence boundary language model

In this paper, we propose two different language modeling approaches, namely skip trigram and across sentence boundary, to capture the long range dependencies. The skip trigram model is able to cover more predecessor words of the present word compared to the normal trigram while the same memory space is required. The across sentence boundary model uses the word distribution of the previous sent...

Words under Sentence

Life within chronic care: is this a service or sentence?

BACKGROUND Understanding the meaning of one's lived experiences improves one's understanding of what it means to be human, in association with the social, cultural and historical context in which being a human occurs. The authors in this study describe the lived experiences of residents within a chronic care facility including the practitioner and family perspectives. METHODS A qualitative ap...

Sentence Emotion Analysis and Recognition Based on Emotion Words Using Ren-CECps∗

Emotion recognition on text has wide applications. In this study, we make an analysis on sentence emotion based on emotion words using Ren-CECps (a Chinese emotion corpus). Some classification methods (including C4.5 decision tree, SVM, NaiveBayes, ZEROR, and DecisionTable) have been compared. Then a supervised machine learning method (Polynomial kernel method) is proposed to recognize the eigh...

A Whole Sentence Maximum Entropy Language Model

We introduce a new kind of language model, which models whole sentences or utterances directly using the Maximum Entropy paradigm. The new model is conceptually simpler, and more naturally suited to modeling whole-sentence phenomena, than the conditional ME models proposed to date. By avoiding the chain rule, the model treats each sentence or utterance as a \bag of features", where features are...