Мешок слов

In this paper, we compare the rela- tive effects of segment order, segmen- tation and segment contiguity on the retrieval performance of a translation memory system. We take a selec- …...

In this paper we propose and evaluate a technique to perform semi-supervised learning for Text Categorization. particular we defined a kernel function,In namely the Domain Kernel, that allowed us to …...

Research on document similarity has shown that complex representations are not more accurate than the simple bag-of- words. Term clustering, e.g. using latent semantic indexing, word co-occurrences or synonym relations …...

We present a system for deciding whether a given sentence can be inferred from text. Each sentence is represented as a directed graph (extracted from a depen- dency parser) in …...

A reading comprehension (RC) system attempts to understand a document and returns an answer sentence when posed with a question. RC resembles the ad hoc question answering (QA) task that …...

Syntactic Features for Text Categorisation Ari Chanen School of Information Technologies University of Sydney Sydney, Australia, 2006 ari@it.usyd.edu.au Jon Patrick School of Information Technologies University of Sydney Sydney, Australia, 2006 …...

Traditional wisdom holds that once docu- ments are turned into bag-of-words (unigram count) vectors, word orders are completely lost. We introduce an approach that, perhaps surprisingly, is able to learn …...

We propose a machine learning based method of sentiment classification of sen- tences using word-level polarity. The polari- ties of words in a sentence are not always the same as …...

Document clustering and classification is usually done by representing the documents using a bag of words scheme. This scheme ignores many of the linguistic and semantic features contained in text …...

Information is fundamental to Finance, and un- derstanding how it flows from official sources to news agencies is a central problem. Readers need to digest information rapidly from high vol- …...

There is a growing research interest in opinion retrieval as on-line users’ opinions are becom- ing more and more popular in business, social networks, etc. Practically speaking, the goal of …...

We explore the task of automatically classify- ing dialogue acts in 1-on-1 online chat forums, an increasingly popular means of providing customer service. In particular, we investi- gate the effectiveness …...

This paper introduces a novel user clas- sification task in the context of web user forums. We present a definition of four basic user characteristics and an anno- tated dataset. …...

In this work, we propose a novel representa- tion of text based on patterns derived from lin- guistic annotation graphs. We use a subgraph mining algorithm to automatically derive fea- …...

This paper presents a two-stage approach to summarizing multiple contrastive viewpoints in opinionated text. In the first stage, we use an unsupervised probabilistic approach to model and extract multiple viewpoints …...

We present a method to estimate word use similarity independent of an external sense inventory. This method utilizes a topic- modelling approach to compute the similar- ity in usage of …...

We propose the hypothesis that word ety- mology is useful for NLP applications as a bridge between languages. We support this hypothesis with experiments in cross- language (English-Italian) document cat- …...

Most sentiment analysis approaches rely on machine-learning techniques, using a bag-of-words (BoW) document represen- tation as their basis. In this paper, we examine whether a more fine-grained rep- resentation of …...

This paper introduces a method for im- proving tree edit distance (TED) for tex- tual entailment. We explore two ways of improving TED: we extend the standard TED to use …...

We present two systems developed at the Uni- versity of Ottawa for the SemEval 2013 Task 2. The first system (for Task A) classifies the po- larity / sentiment orientation …...

Text classification methods for tasks like factoid question answering typi- cally use manually defined string match- ing rules or bag of words representa- tions. These methods are ineffective when question …...

Earnings call summarizes the financial performance of a company, and it is an important indicator of the future financial risks of the company. We quantitatively study how earnings calls are …...

With the rapid development of web-based services, concerns about user privacy have height- ened. The privacy policies of online websites, which serve as a legal agreement between service providers and …...

This paper presents a large-scale evalua- tion of bag-of-words distributional models on two datasets from priming experiments involving syntagmatic and paradigmatic relations. We interpret the variation in performance achieved by …...

Research in emotion analysis of text sug- gest that emotion lexicon based features are superior to corpus based n-gram fea- tures. However the static nature of the general purpose emotion …...

Text Analytics using semantic information is the latest trend of research due to its potential to represent better the texts content compared with the bag-of-words approaches. On the contrary, representation …...

This paper presents an overlap-based ap- proach using bag of words and the Spanish WordNet to solve the STS-Spanish sub- task (STS-Es) of SemEval-2014 Task 10. Since bag of words …...

This study is about the development of a learner-focused text readability indexing tool for second language learners (L2) of English. Student essays are used to cali- brate the system, making …...

Current approaches to cross-lingual informa- tion retrieval (CLIR) rely on standard retrieval models into which query translations by sta- tistical machine translation (SMT) are inte- grated at varying degree. In …...

In this paper, we consider the task of learn- ing control policies for text-based games. In these games, all interactions in the vir- tual world are through text and the …...

We introduce an extension to the bag-of- words model for learning words represen- tations that take into account both syn- tactic and semantic properties within lan- guage. This is done …...

Text is composed of words and phrases. In bag-of-word model, phrases in texts are split into words. This may discard the inner seman- tics of phrases which in turn may …...

For most entity disambiguation systems, the secret recipes are feature representa- tions for mentions and entities, most of which are based on Bag-of-Words (BoW) representations. several drawbacks:Commonly, BoW has (1) …...

AbstractThis report describes our participation to SemEval-2017 Task 4: Sentiment Analysis in Twitter, specifically in subtasks A, B, and C. The approach for text sentiment classification is based on a …...

AbstractThis paper presents the approach developed at the Faculty of Engineering of University of Porto, to participate in SemEval 2017, Task 5: Fine-grained Sentiment Analysis on Financial Microblogs and News. …...

AbstractThis paper describes our multi-view ensemble approach to SemEval-2017 Task 4 on Sentiment Analysis in Twitter, specifically, the Message Polarity Classification subtask for English (subtask A). Our system is a …...

AbstractThe SSN MLRG1 team for Semeval-2017 task 4 has applied Gaussian Process, with bag of words feature vectors and fixed rule multi-kernel learning, for sentiment analysis of tweets. Since tweets …...

AbstractThis paper describes the model UdL we proposed to solve the semantic textual similarity task of SemEval 2017 workshop. The track we participated in was estimating the semantics relatedness of …...

AbstractWe introduce Zipporah, a fast and scalable data cleaning system. We propose a novel type of bag-of-words translation feature, and train logistic regression models to classify good data and synthetic …...

AbstractIn this paper, we describe a methodology to predict emoji in tweets. Our approach is based on the classic bag-of-words model in conjunction with word embeddings. The used classification algorithm …...

This paper presents a benchmark dataset for the task of inter-sentence relation extraction. The paper explains the distant supervision method followed for creating the dataset for inter-sentence relation extraction, involving …...

This work presents a comparative study between two different approaches to build an automatic classification system for Modality values in the Portuguese language. One approach uses a single multi-class classifier …...

AbstractThis paper discusses on task 1, “Affect in Tweets” sharedtask, conducted in SemEval-2018. This task comprises of various subtasks, which required participants to analyse over different emotions and sentiments based …...

A sampling survey of typology and component ratio analysis in Japanese puns revealed that the type of Japanese pun that had the largest proportion was a pun type with two …...

It is widely held that smells and flavors are impossible to put into words. In this paper we test this claim by seeking predictive patterns in wine reviews, which ostensibly …...

AbstractWe evaluated various compositional models, from bag-of-words representations to compositional RNN-based models, on several extrinsic supervised and unsupervised evaluation benchmarks. Our results confirm that weighted vector averaging can outperform context-sensitive …...

AbstractWe present our submission to the Semeval 2018 task on emoji prediction. We used a random forest, with an ensemble of bag-of-words, sentiment and psycholinguistic features. Although we performed well …...

AbstractIn this paper, we present our system for assigning an emoji to a tweet based on the text. Each tweet was originally posted with an emoji which the task providers …...

AbstractWhile paragraph embedding models are remarkably effective for downstream classification tasks, what they learn and encode into a single vector remains opaque. In this paper, we investigate a state-of-the-art paragraph …...

AbstractIn this paper, we establish the effectiveness of using hard negatives, coupled with a siamese network and a suitable loss function, for the tasks of answer selection and answer triggering. …...

Identifying argument components has become an important area of research in argument mining. When argument components are identified, they can not only be used for stance classification but also can …...

AbstractThis paper proposes a simple and effective approach to address the problem of posterior collapse in conditional variational autoencoders (CVAEs). It thus improves performance of machine translation models that use …...

AbstractDebate transcripts from the UK Parliament contain information about the positions taken by politicians towards important topics, but are difficult for people to process manually. While sentiment analysis of debate …...

AbstractWe explore the task of sentiment analysis on Hinglish (code-mixed Hindi-English) tweets as participants of Task 9 of the SemEval-2020 competition, known as the SentiMix task. We had two main …...

AbstractIn this work, we argue that augmenting argument generation technology with the ability to encode beliefs is of twofold. First, it gives more control on the generated arguments leading to …...

AbstractWe consider the hierarchical representation of documents as graphs and use geometric deep learning to classify them into different categories. While graph neural networks can efficiently handle the variable structure …...

AbstractMuch of the progress in contemporary NLP has come from learning representations, such as masked language model (MLM) contextual embeddings, that turn challenging problems into simple classification tasks. But how …...

AbstractWe present a neural-network-driven model for annotating frustration intensity in customer support tweets, based on representing tweet texts using a bag-of-words encoding after processing with subword segmentation together with non-lexical …...

In this research, we investigate techniques to detect hate speech in movies. We introduce a new dataset collected from the subtitles of six movies, where each utterance is annotated ei- …...

AbstractSequential information, a.k.a., orders, is assumed to be essential for processing a sequence with recurrent neural network or convolutional neural network based encoders. However, is it possible to encode natural …...

AbstractWith the ever-increasing availability of digital information, toxic content is also on the rise. Therefore, the detection of this type of language is of paramount importance. We tackle this problem …...

AbstractAdapting word order from one language to another is a key problem in cross-lingual structured prediction. Current sentence encoders (e.g., RNN, Transformer with position embeddings) are usually word order sensitive. …...

AbstractThe quality of artificially generated texts has considerably improved with the advent of transformers. The question of using these models to generate learning data for supervised learning tasks naturally arises, …...

Document scaling techniques have been widely used in political science to infer parti- sanship measures and to rank documents on a scale of ideal points, based on bag-of-word ap- proaches. …...

AbstractThis paper details our implementations for finding Patronizing and Condescending Language in texts, as part of the SemEval Workshop Task 4. We have used a variety of methods from simple …...

AbstractThis paper presents our work on the SemEval-2023 Task 10 Explainable Detection of Online Sexism (EDOS) using lexicon-based models. Our approach consists of three main steps: lexicon construction based on …...

AbstractStance prediction - the computational task of inferring attitudes towards a given target topic of interest - relies heavily on text data provided by social media or similar sources, but …...

AbstractThis paper presents the work produced by students of the University of Orlans Masters in Natural Language Processing program by way of participating in SemEval Task 6, LegalEval, which aims …...