Decision Trees

We describe work which uses decision trees to estimate marginal probabilities in a maximum entropy model for pre- dicting the part-of-speech of a word given the context in which it …...

The development of natural language pro- ccssing (NLP) systems that perform ma- chine translation (MT) and information re- trieval (IR) has highlighted the need for the automatic recognition of proper …...

Miscommunication in speech recognition sys- tems is unavoidable, but a detailed character- ization of user corrections will enable speech systems to identify when a correction is taking place and to …...

This paper describes novel and practical Japanese parsers that uses decision trees. First, we con- struct a single decision tree to estimate modifica- tion probabilities; how one phrase tends to …...

In this paper we show how machine learning techniques for constructing and combining sev- eral classifiers can be applied to improve the accuracy of an existing English POS tagger (MSxquez …...

For languages without word boundary delimiters, dictionaries are needed for segmenting running texts. This figure makes segmentation accuracy depend significantly on the quality of the dictionary used for analysis. If …...

This paper examines feature selection for log linear models over rich constraint-based grammar (HPSG) representations by building decision trees over fea- tures in corresponding probabilistic context free grammars (PCFGs). We …...

The regular occurrence of disfluencies is a distinguishing characteristic of spontaneous speech. Detecting and removing such disflu- encies can substantially improve the usefulness of spontaneous speech transcripts. This pa- per …...

State-of-the-art story link detection systems, that is, systems that determine whether two sto- ries are about the same event or linked, are usu- ally based on the cosine-similarity measured between …...

In this paper, we explore the use of Random Forests (RFs) (Amit and Geman, 1997; Breiman, 2001) in language modeling, the problem of predicting the next word based on words …...

This paper investigates automatic identi- fication of Information Structure (IS) in texts. The experiments use the Prague Dependency Treebank which is annotated with IS following the Praguian approach of Topic …...

In this paper we present a semantic archi- tecture that was employed for processing two different SemEval 2007 tasks: Task 4 (Classification of Semantic Relations be- tween Nominals) and Task …...

We present a HMM part-of-speech tag- ging method which is particularly suited for POS tagsets with a large number of fine-grained tags. It is based on three ideas: (1) splitting …...

Entropy Guided Transformation Learning (ETL) is a new machine learning strategy that combines the advantages of decision trees (DT) and Transformation Based Learn- ing (TBL). In this work, we apply …...

This paper presents a first-order logic learn- ing approach to determine rhetorical relations between discourse segments. Beyond lin- guistic cues and lexical information, our ap- proach exploits compositional semantics and …...

In this paper we present an opinion summari- zation technique in spoken dialogue systems. Opinion mining has been well studied for years, but very few have considered its appli- cation …...

AbstractResearch on automatic humor recognition has developed several features which discriminate funny text from ordinary text. The features have been demonstrated to work well when classifying the funniness of single …...

This report describes the UNITN system, a Part-Of-Speech Context Counter, that par- ticipated at Semeval 2010 Task 8: Multi- Way Classification of Semantic Relations Between Pairs of Nominals. Given a …...

We offer a supervised machine learn- ing approach for recognizing erroneous words in the output of a speech recognizer. We have investigated several sets of fea- tures combined with two …...

AbstractWe present a part of broader research on word order aiming at finding factors influencing word order in Czech (i.e. in an inflectional language) and their intensity. The main aim …...

The DsUniPi team participated in the SemEval 2015 Task#11: Sentiment Analysis of Figura- tive Language in Twitter. The proposed ap- proach employs syntactical and morphological features, which indicate sentiment polarity …...

This paper describes team MAZA entries for the 2016 SemEval Task 11: Complex Word Identification (CWI). The task is a binary clas- sification task in which systems are trained to …...

We report the findings of the Complex Word Identification task of SemEval 2016. To cre- ate a dataset, we conduct a user study with 400 non-native English speakers, and find …...

AbstractDecision trees have been previously employed in many machine-learning tasks such as part-of-speech tagging, lemmatization, morphological-attribute resolution, letter-to-sound conversion and statistical-parametric speech synthesis. In this paper we introduce an optimized …...

AbstractThis paper describes the CompNa model that has been submitted to the Lexical Complexity Prediction (LCP) shared task hosted at SemEval 2021 (Task 1). The solution is based on combining …...

AbstractThe International Classification of Diseases (ICD) is a system for systematically recording patients’ diagnoses. Clinicians or professional coders assign ICD codes to patients’ medical records to facilitate funding, research, and …...

AbstractICD coding is designed to assign the disease codes to electronic health records (EHRs) upon discharge, which is crucial for billing and clinical statistics. In an attempt to improve the …...

AbstractLiterature permeates through almost every facet of our lives, whether through books, magazines, or internet articles. Moreover, every piece of written work contains ideas and opinions that we tend to …...