Data Set Used
The IBM POWER A processor is the dominant reduced instruction set computing microprocessor in the world today, with a rich history of implementation and innovation over the last 20 years. In this paper, we describe the key features of the POWER7 A processor chip. On the chip is an eight-core processor, with each core capable of four-way simultaneous… (More)
• Topic models take a corpus of documents as input, and jointly cluster: words by the documents that they occur in, and documents by the words that they contain • If the corpus is small and/or the documents are short, these clusters will be noisy • Latent feature representations of words learnt from large external corpora (e.g., word2vec, Glove) capture… (More)
This paper presents a framework for automatically constructing timeline summaries from collections of web news articles. We also evaluate our solution against manually created timelines and in comparison with related work.
This paper describes our robust, easy-to-use and language independent toolkit namely RDRPOSTagger which employs an error-driven approach to automatically construct a Single Classification Ripple Down Rules tree of transformation rules for POS tagging task. During the demonstration session, we will run the tagger on data sets in 15 different languages.
(2014). Sentiment classification on polarity reviews: an empirical study using rating-based features. Copyright and Moral Rights for the articles on this site are retained by the individual authors and/or other copyright owners. For more information on Open Research Online's data policy on reuse of materials please consult the policies page. Abstract We… (More)
In this paper, we present a study applying reject option to build a two-stage sentiment polarity classification system. We construct a Naive Bayes classifier at the first stage and a Support Vector Machine at the second stage, in which documents rejected at the first stage are forwarded to be classified at the second stage. The obtained accuracies are… (More)
This paper presents a new conversion method to automatically transform a constituent-based Vietnamese Treebank into dependency trees. On a dependency Treebank created according to our new approach, we examine two state-of-the-art dependency parsers: the MSTParser and the MaltParser. Experiments show that the MSTParser outperforms the MaltParser. To the best… (More)
Knowledge bases of real-world facts about entities and their relationships are useful resources for a variety of natural language processing tasks. However, because knowledge bases are typically incomplete, it is useful to be able to perform link prediction, i.e., predict whether a relationship not in the knowledge base is likely to be true. This paper… (More)
For the task of turning a natural language question into an explicit intermediate representation of the complexity in question answering systems, all published works so far use rule-based approach to the best of our knowledge. We believe it is because of the complexity of the representation and the variety of question types and also there are no publicly… (More)
This paper presents a new approach to learn a rule based system for the task of part of speech tagging. Our approach is based on an incremental knowledge acquisition methodology where rules are stored in an exception-structure and new rules are only added to correct errors of existing rules; thus allowing systematic control of interaction between rules.… (More)