Semi-unsupervised approach toward learning meaning
نویسنده
چکیده
In this report, we implement the recursive auto encoder (RAE) method for learning meaning of sentences. We present the missing details for calculating the gradients and for back-propagation techniques. We implement a preliminary experiment to verify the correctness of our derivation for gradients. We get 64.72% accuracy on test set using the dimension of meaning d = 40.
منابع مشابه
Word Sense Induction and Disambiguation Rivaling Supervised Methods
Word Sense Disambiguation (WSD) aims to determine the meaning of a word in context and successful approaches are known to benefit many applications in Natural Language Processing. Although, supervised learning has been shown to provide superior WSD performance, current sense-annotated corpora do not contain a sufficient number of instances per word type to train supervised systems for all words...
متن کاملUnsupervised Approach for Dialogue Act Classification
This paper presents an unsupervised approach for dialogue act (DA) classification. We used a latent variable model to compress the dimensions of the feature vector. We introduced a paraphraser to reduce the variety of expressions and to solve the pragmatic problem for DA classification. The paraphraser seemed to work well on some DA classifications in the unsupervised approach. The results obta...
متن کاملSemi-supervised Learning with Induced Word Senses for State of the Art Word Sense Disambiguation
Word Sense Disambiguation (WSD) aims to determine the meaning of a word in context, and successful approaches are known to benefit many applications in Natural Language Processing. Although supervised learning has been shown to provide superior WSD performance, current sense-annotated corpora do not contain a sufficient number of instances per word type to train supervised systems for all words...
متن کاملAn Artificial Life Approach for Semi-supervised Learning
An approach for the integration of supervising information into unsupervised clustering is presented (semi supervised learning). The underlying unsupervised clustering algorithm is based on swarm technologies from the field of Artificial Life systems. Its basic elements are autonomous agents called Databots. Their unsupervised movement patterns correspond to structural features of a high dimens...
متن کاملMinimum Density Hyperplanes
Associating distinct groups of objects (clusters) with contiguous regions of high probability density (high-density clusters), is a central assumption in statistical and machine learning approaches for the classification of unlabelled data. In unsupervised classification this cluster definition underlies a nonparametric approach known as density clustering. In semi-supervised classification, cl...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2012