... on one group of MT systems evaluate the translation qualities of new systems? In this paper, we argue for the viability of a regression-based framework for sentence-level MTevaluation Through ... and Chris Brockett 2001 A machine learning approach to the automatic evaluation of machine translation In Proceedings of the 39th Annual Meeting of the Association for Com...
... Dependencies in Sentiment Classification Experimental Setup In this section, we describe experiments we have carried out to determine the in uence of domain, topic and time on machine learning based sentiment ... negative sentiment (selected by independent trained annotators), each containing 100 stories We trained a model on a dataset relating to one topic and tested that m...
... '98), March 1998 M E Califf and R J Mooney 2004 Bottom-Up Relational Learning of Pattern Matching Rules for Information Extraction Journal of Machine Learning Research, MIT Press W Drozdzynski, H.-U.Krieger, ... we use PI for Person_In, PO for Person_Out, POS for Position and ORG for Organisation In our experiments, we attempt to investigate the influence of the size...
... 1.0, replicates a 3.5 hour attack scenario in which a trainee attacker starts a Distributed Denial of Service (DDOS) attack against a raw adversary The second data set, LLS DDOS 2.0.2, is a two hour ... 0.2 K- Means ID3 K- Means ID3 K- Means+ID3 K- Means+ID3 Fig Performance of K- Means, ID3, K- Means+ID3, and the KPrototype+ID3 over the NAD 1998 test data set Fig Performance o...
... note that the SVMs trained with 256dimensional raw AE data had quite poor performance, where the AUC was 0.39 and 0.31 for datasets SR1 and SR2 We also examined the performance of a combination ... variance (a) (b) Figure 10: The training classification performance of different feature sets on the dataset SR1 (a) and SR2 (b) The best performance was obtained with WP approach The performan...
... 134 Summary and Future Work Bibliography Machine Learning Methods for Pattern Analysis 137 A Ji He Machine Learning Methods for Pattern Analysis and Clustering Ji He, 2004 National ... 4.3 Machine Learning Methods for Pattern Analysis Ji He Machine Learning Methods for Pattern Analysis and Clustering Ji He, 2004 National University of...
... concerned with the development and interpretation of machine learning models for drug discovery To this end, it describes the design and application of computational models for specialized use ... focus of this thesis is the development and interpretation of machine learning models for pharmaceutical tasks In drug discovery, project teams usual...
... only original sentences are parsed, and the parse trees of compressed sentences are extracted from the original parse trees An example of this method is shown in Figure The original sentence is ... goal sentence length for summaries In the first experiment, the system was given only a sentence and no sentence length information The sentence compression problem without the...
... A Ranking Approach to Coreference ¡ As mentioned before, our approach differs from the standard approach primarily by (1) explicitly learning a ranker and (2) optimizing for clustering-level ... learning approach, outperforming them by as much as 4–7% on the three data sets for one of the performance metrics 3.1 Selecting Coreference Systems A learning- based coreference...
... learning to perform various graph transformations One of the transformations is node relabelling, which adds function tags to parser output They report an fscore of 88.5% for the task of function ... 3.2 Adding Function Tags to Parser Output 4.1 The solution we adopt instead is to add Cast3LB functional tags to simple constituent trees output by the parser, as a p...
... Natural Language Annotation for Machine Learning James Pustejovsky and Amber Stubbs Beijing • Cambridge • Farnham • Köln • Sebastopol • Tokyo www.it-ebooks.info Natural Language Annotation for ... (NLP) In particular, we examine how information can be added to natural language text through annotation in order to increase the performance of machine learning algori...
... decision-tree learning research to itself 3.3 Training Attributes The training attributes that we prepared for Japanese ellipsis resolution are listed in Table The training attributes in the table ... test dialogues (1685 subject ellipses), and none were included in the training dialogues Table indicates the training size and performance calculated by F-measure This illustra...
... linguistic information on the comma for the Basque language was formalised This information was extracted after analysing the theories of some experts in Basque syntax and punctuation (Aldezabal et al., ... the same time, for each token, we stored whether it was followed by a comma or not That is, for each word (token), it was stored whether a comma was placed next to it or...
... Other non-parametric Bayesian models Further Topics [15 minutes] o o Bayesian Semi-supervised Learning o Bayesian Active Learning and Bayesian Decision Theory Reconciling Bayesian and Frequentist ... summer schools He is interested in Bayesian machine learning, computational approaches to sensorimotor control, and applications of machine learning to bioinformatics Zoubi...