Previous researches on event relation classification primarily rely on lexical and syntactic *** this paper,we use a Shallow Convolutional Neural Network(SCNN)to extract event-level and cross-event semantic features f...
详细信息
Previous researches on event relation classification primarily rely on lexical and syntactic *** this paper,we use a Shallow Convolutional Neural Network(SCNN)to extract event-level and cross-event semantic features for event relation *** the one hand,the shallow structure alleviates the over-fitting problem caused by the lack of diverse relation *** the other hand,the utilization and combination of event-level and cross-event semantic information help improve relation *** experimental results show that our approach outperforms the state of the art.
Here we propose an advance Skip-gram model to incorporate both word sentiment and negation information. In particular, there is aa softmax layer for the word sentiment polarity upon the Skip-gram model. Then, two para...
详细信息
This paper describes our submissions to Task 6, i.e., Detecting Stance in Tweets, in SemEval 2016, which aims at detecting the stance of tweets towards given target. There are three stance labels: Favor (directly or i...
详细信息
It is well known that Differential Evolution (DE) algorithm has been widely applied to solve global optimization problems during the last decades. DE is usually criticized for the slow convergence. To improve the algo...
详细信息
This paper describes our systems submitted to the Sentence-level and Text-level Aspect-Based Sentiment Analysis (ABSA) task (i.e., Task 5) in SemEval-2016. The task involves two phases, namely, Aspect Detection phase ...
详细信息
This paper reports our submissions to Task 4, i.e., Sentiment Analysis in Twitter (SAT), in SemEval 2016, which consists of five subtasks grouped into two levels: (1) sentence level, i.e., message polarity classificat...
详细信息
This paper describes our two discourse parsers (i.e., English discourse parser and Chinese discourse parser) for submission to CoNLL-2016 shared task on Shallow Discourse Parsing. For English discourse parser, we buil...
详细信息
This paper describes our system submissions to task 7 in SemEval 2016, i.e., Determining Sentiment Intensity. We participated the first two subtasks in English, which are to predict the sentiment intensity of a word o...
详细信息
This paper describes the system we submitted to the task 3 (Community Question Answering) in SemEval 2016, which contains three subtasks, i.e., Question-Comment Similarity (subtask A), Question-Question Similarity (su...
详细信息
This paper presents our submissions for semantic textual similarity task in SemEval 2016. Based on several traditional features (i.e., string-based, corpus-based, machine translation similarity and alignment metrics),...
详细信息
暂无评论