SupervisedMachineLearning

This paper describes a set of experiments car- ried out to explore the domain dependence of alternative supervised Word Sense Disam- biguation algorithms. The aim of the work is threefold: …...

In this paper we report results of a supervised machine-learning approach to Chinese word segmentation. A maximum entropy tagger is trained on manually annotated data to automatically assign to Chinese …...

In this paper, experiments on automatic extraction of keywords from abstracts us- ing a supervised machine learning algo- rithm are discussed. The main point of this paper is that by …...

We present two methods for automatically discovering the telic and agentive roles of nouns from corpus data. These relations form part of the qualia structure assumed in generative lexi- con …...

. Fixed multiword expressions are strings of words which to- gether behave like a single word. This research establishes a method for the automatic extraction of such expressions. Our method …...

In addition to information, text con- tains attitudinal, and more specifically, emotional content. This paper explores the text-based emotion prediction prob- lem empirically, using supervised machine learning with the SNoW …...

In this paper we present a machine learning system that finds the scope of negation in biomedical texts. The system consists of two memory-based engines, one that decides if the …...

Most existing information retrieval (IR) systems do not take much advantage of natural language processing (NLP) tech- niques due to the complexity and limited observed effectiveness of applying NLP to …...

Automatic image annotation is an attrac- tive approach for enabling convenient ac- cess to images found in a variety of docu- ments. Since image captions and relevant discussions found in …...

A large body of prior research on coref- erence resolution recasts the problem as a two-class classification problem. How- ever, standard supervised machine learn- ing algorithms that minimize classifica- tion …...

Argumentative Zoning (AZ) – analysis of the argumentative structure of a scientific paper – has proved useful for a number of informa- tion access tasks. Current approaches to AZ rely …...

A medical publication may or may not present an outcome. When an outcome is present, its polarity may be positive, negative or neu- tral. Information about the polarity of an …...

. In this paper, we present Thai named entity recognition (NER) systems using supervised Conditional Random Fields (CRFs) with various answer patterns to find out whether different answer patterns would …...

We describe the in-class evaluation of two versions of a tutorial dialogue sys- tem with 338 volunteers from a first-year undergraduate health-sciences class. One version uses supervised machine-learning techniques to …...

In this paper, we investigate a full-fledged supervised machine learning framework for identifying English phrasal verbs in a given context. We concentrate on those that we de- fine as the …...

AbstractDocument zone identification aims to automatically classify sequences of text-spans (e.g. sentences) within a document into predefined zone categories. Current approaches to document zone identification mostly rely on supervised machine …...

The UOW submissions to the Semantic Tex- tual Similarity task at SemEval-2012 use a supervised machine learning algorithm along with features based on lexical, syntactic and semantic similarity metrics to …...

Document revision histories are a useful and abundant source of data for natural language processing, but selecting relevant data for the task at hand is not trivial. In this paper …...

This paper describes the details of our system submitted to the SemEval-2013 shared task on sentiment analysis in Twitter. Our approach to predicting the sentiment of Tweets and SMS is …...

Speaker identification is the task of at- tributing utterances to characters in a lit- erary narrative. It is challenging to auto- mate because the speakers of the majority of utterances …...

Predicting the quality of machine trans- lations is a challenging topic. Quality estimation (QE) of translations is based on features of the source and target texts (without the need for …...

AbstractThis paper proposes a method for extracting Daily Changing Words (DCWs), words that indicate which questions are real-time dependent. Our approach is based on two types of template matching using …...

AbstractNatural language analysis of patents holds promise for the development of tools designed to assist analysts in the monitoring of emerging technologies. One component of such tools is the identification …...

AbstractThis work investigates how automated methods can be used to classify social media text into argumentation types. In particular it is shown how supervised machine learning was used to annotate …...

This paper describes the details of our system submitted to the SemEval-2014 shared task about aspect-based sentiment analysis on review texts. We participated in subtask 2 (prediction of the polarity …...

In this paper, we introduce our contribu- tions to the SemEval-2014 Task 4 – As- pect Based Sentiment Analysis (Pontiki et al., 2014) challenge. We participated in the aspect term …...

This paper describes the systems submit- ted by the University of San Francisco (USF) to Semeval-2014 Task 4, Aspect Based Sentiment Analysis (ABSA), which provides labeled data in two domains, …...

This paper describes our system partici- pating in the aspect-based sentiment anal- ysis task of Semeval 2014. The goal was to identify the aspects of given tar- get entities and …...

In this paper, we look at three different meth- ods of extracting the argumentative structure from a piece of natural language text. These methods cover linguistic features, changes in the …...

A fundamental issue in opinion mining is to search a corpus for opinion units, each of which typically comprises the evalua- tion by an author for a target object from …...

This paper describes QCRI’s participation in SemEval-2015 Task 3 “Answer Selection in Community Question Answering”, which tar- geted real-life Web forums, and was offered in both Arabic and English. We …...

This paper describes SVCSTS, a system that was submitted in SemEval-2015 Task 2: Se- mantic Textual Similarity(STS)(Agirre et al., 2015). The task has 3 subtasks viz., English STS, Spanish STS …...

AbstractIn this paper, we present a music retrieval and recommendation system using machine learning techniques. We propose a query by humming system for music retrieval that uses deep neural networks …...

AbstractWe propose a hierarchical clustering approach designed to group linguistic features for supervised machine learning that is inspired by variationist linguistics. The method makes it possible to abstract away from …...

This paper describes an approach used to solve Aspect Category Detection (Subtask 1, Slot 1) of SemEval 2016 Task 5. The core of the pre- sented system is based on …...

AbstractHashtags, which are commonly composed of multiple words, are increasingly used to convey the actual messages in tweets. Understanding what tweets are saying is getting more dependent on understanding hashtags. …...

AbstractThis paper describes our submission to SemEval-2017 Task 3 Subtask D, “Question Answer Ranking in Arabic Community Question Answering”. In this work, we applied a supervised machine learning approach to …...

AbstractThe state-of-the-art named entity recognition (NER) systems are supervised machine learning models that require large amounts of manually annotated data to achieve high accuracy. However, annotating NER data by human …...

AbstractAnimacy is a necessary property for a referent to be an agent, and thus animacy detection is useful for a variety of natural language processing tasks, including word sense disambiguation, …...

AbstractThis paper describes our submissions to SemEval 2018 task 1. The task is affect intensity prediction in tweets, including five subtasks. We participated in all subtasks of English tweets. We …...

AbstractAn abundance of electronic health records (EHR) is produced every day within healthcare. The records possess valuable information for research and future improvement of healthcare. Multiple efforts have been done …...

AbstractThis paper describes the development of a chunker for spoken data by supervised machine learning using the CRFs, based on a small reference corpus composed of two kinds of discourse: …...

AbstractDepression and related mental health issues are often reflected in the language employed by the individuals who suffer from these conditions and, accordingly, research in Natural Language Processing (NLP) and …...

AbstractThe massive spread of false information on social media has become a global risk especially in a global pandemic situation like COVID-19. False information detection has thus become a surging …...

AbstractWe introduce the well-established social scientific concept of social solidarity and its contestation, anti-solidarity, as a new problem setting to supervised machine learning in NLP to assess how European solidarity …...

AbstractWritten communication is of utmost importance to the progress of scientific research. The speed of such development, however, may be affected by the scarcity of reviewers to referee the quality …...

AbstractActive learning promises to alleviate the massive data needs of supervised machine learning: it has successfully improved sample efficiency by an order of magnitude on traditional tasks like topic classification …...

AbstractLanguage contact is a pervasive phenomenon reflected in the borrowing of words from donor to recipient languages. Most computational approaches to borrowing detection treat all languages under study as equally …...