D15-1284 Qualitative Evaluation The above humor recognition classifier provides us with decent
D15-1284 particular attention . The task of Humor Recognition refers to determining whether
D15-1284 explained . One essential component in humor recognition is the construction of negative
D15-1284 Anchor Extraction In addition to humor recognition , identifying anchors , or which
H05-1067 successfully applied to the task of humor recognition . Through experiments performed
D15-1284 personal affect . In addition to humor recognition , identifying anchors , or which
D15-1284 score , which is computed via a humor recognition classifier trained on all data
D15-1284 described the performance of both humor recognition and humor anchor extraction tasks
D15-1284 latent semantic structures affect humor recognition performance and summarize the
D15-1284 existing benchmark datasets for humor recognition and most studies select negative
D15-1284 structures . The performances of humor recognition and anchor extraction are superior
D15-1284 expresses a certain degree of humor . Humor recognition is a challenging natural language
D15-1284 anchors in humorous text . Both humor recognition and humor anchor extraction suffer
D15-1284 Humor Recognition We formulate humor recognition as a traditional text classification
D15-1284 language through two subtasks : humor recognition and humor anchor extraction .
D15-1284 . In this work , we formulate humor recognition as a classification task in which
H05-1067 create computational models for humor recognition or generation . In this paper
D15-1284 learn computational models for humor recognition , but also provide us with the
D15-1284 reflect the views of NSF . <title> Humor Recognition and Humor Anchor Extraction </title>
D15-1284 them as negative instances of humor recognition could result in deceptively high
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