Amrita_CEN at SemEval-2016 Task 1: Semantic Relation from Word Embeddings in Higher Dimension

Ganesh, H B Barathi; Kumar, M. Anand

doi:10.18653/v1/s16-1109

Cited by 5 publications

(1 citation statement)

References 5 publications

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“…We used distributed representation (Le and Mikolov, 2014;Ganesh H. B. et al, 2016a) to create feature vector which can be feed as input to machine learning algorithms for classification and regression. Bag-of-words is one of the most common method used to create fixed length feature vectors but the ordering and semantics of the words are ignored in this method.…”

Section: Introductionmentioning

confidence: 99%

Amrita_student at SemEval-2018 Task 1: Distributed Representation of Social Media Text for Affects in Tweets

Unnithan¹,

Kumari

Ganesh

et al. 2018

Proceedings of the 12th International Workshop on Semantic Evaluation

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In this paper we did an analysis of "Affects in Tweets" which was one of the task conducted by SemEval 2018. Task was to build a model which is able to do regression and classification of different emotions from the given tweets data set. We developed a base model for all the subtasks using distributed representation (Doc2Vec) and applied machine learning techniques for classification and regression. Distributed representation is an unsupervised algorithm which is capable of learning fixed length feature representation from variable length texts. Machine learning techniques used for regression is 'Linear Regression' while 'Random Forest Tree' is used for classification purpose. Empirical results obtained for all the subtasks by our model are shown in this paper.

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Section: Introductionmentioning

confidence: 99%

Amrita_student at SemEval-2018 Task 1: Distributed Representation of Social Media Text for Affects in Tweets

Unnithan¹,

Kumari

Ganesh

et al. 2018

Proceedings of the 12th International Workshop on Semantic Evaluation

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From Vector Space Models to Vector Space Models of Semantics

Ganesh

Kumar

Soman

2018

Lecture Notes in Computer Science

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CENNLP at SemEval-2018 Task 1: Constrained Vector Space Model in Affects in Tweets

Naveen¹,

Ganesh

et al. 2018

Proceedings of the 12th International Workshop on Semantic Evaluation

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This paper discusses on task 1, "Affect in Tweets" sharedtask, conducted in SemEval-2018. This task comprises of various subtasks, which required participants to analyse over different emotions and sentiments based on the provided tweet data and also measure the intensity of these emotions for subsequent subtasks. Our approach is to come up with a model for all the subtasks on count based representation and use machine learning techniques for regression and classification related tasks. In this work, we use bag of words technique for supervised text classification and regression.. Further, fine tuning on various parameters for the bag of word, representation model we acquired better scores over various other baseline models (Vinayan et al.) participated in the sharedtask.

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Amrita_CEN at SemEval-2016 Task 1: Semantic Relation from Word Embeddings in Higher Dimension

Cited by 5 publications

References 5 publications

Amrita_student at SemEval-2018 Task 1: Distributed Representation of Social Media Text for Affects in Tweets

Amrita_student at SemEval-2018 Task 1: Distributed Representation of Social Media Text for Affects in Tweets

From Vector Space Models to Vector Space Models of Semantics

CENNLP at SemEval-2018 Task 1: Constrained Vector Space Model in Affects in Tweets

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