Papers Topic Classification

Topic-based Evaluation for Conversational Bots

Dialog evaluation is a challenging problem, especially for non task-oriented dialogs where conversational success is not well-defined. We propose to evaluate dialog quality using topic-based metrics that describe the abi…

Jointly Trained Sequential Labeling and Classification by Sparse Attention Neural Networks

Sentence-level classification and sequential labeling are two fundamental tasks in language understanding. While these two tasks are usually modeled separately, in reality, they are often correlated, for example in inten…

Initializing Convolutional Filters with Semantic Features for Text Classification

Convolutional Neural Networks (CNNs) are widely used in NLP tasks. This paper presents a novel weight initialization method to improve the CNNs for text classification. Instead of randomly initializing the convolutional …

Data Sets: Word Embeddings Learned from Tweets and General Data

A word embedding is a low-dimensional, dense and real- valued vector representation of a word. Word embeddings have been used in many NLP tasks. They are usually gener- ated from a large text corpus. The embedding of a w…

Cross-Lingual Classification of Topics in Political Texts

In this paper, we propose an approach for cross-lingual topical coding of sentences from electoral manifestos of political parties in different languages. To this end, we exploit continuous semantic text representations …

Active learning in annotating micro-blogs dealing with e-reputation

Elections unleash strong political views on Twitter, but what do people really think about politics? Opinion and trend mining on micro blogs dealing with politics has recently attracted researchers in several fields incl…

Distant Supervision for Topic Classification of Tweets in Curated Streams

We tackle the challenge of topic classification of tweets in the context of analyzing a large collection of curated streams by news outlets and other organizations to deliver relevant content to users. Our approach is no…

On- and Off-Topic Classification and Semantic Annotation of User-Generated Software Requirements

Analysis of Policy Agendas: Lessons Learned from Automatic Topic Classification of Croatian Political Texts

Intra-Topic Variability Normalization based on Linear Projection for Topic Classification

Longitudinal Analysis of Discussion Topics in an Online Breast Cancer Community using Convolutional Neural Networks

Identifying topics of discussions in online health communities (OHC) is critical to various applications, but can be difficult because topics of OHC content are usually heterogeneous and domain-dependent. In this paper, …

Embracing Error to Enable Rapid Crowdsourcing

Microtask crowdsourcing has enabled dataset advances in social science and machine learning, but existing crowdsourcing schemes are too expensive to scale up with the expanding volume of data. To scale and widen the appl…

Co-Training for Topic Classification of Scholarly Data

Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding

This paper presents a new semi-supervised framework with convolutional neural networks (CNNs) for text categorization. Unlike the previous approaches that rely on word embeddings, our method learns embeddings of small te…

Bayesian Optimization of Text Representations

When applying machine learning to problems in NLP, there are many choices to make about how to represent input texts. These choices can have a big effect on performance, but they are often uninteresting to researchers or…

Semantic Frame Identification with Distributed Word Representations

A LDA-Based Topic Classification Approach From Highly Imperfect Automatic Transcriptions

Although the current transcription systems could achieve high recognition performance, they still have a lot of difficulties to transcribe speech in very noisy environments. The transcription quality has a direct impact …

NOMAD: Linguistic Resources and Tools Aimed at Policy Formulation and Validation

The NOMAD project (Policy Formulation and Validation through non Moderated Crowd-sourcing) is a project that supports policy making, by providing rich, actionable information related to how citizens perceive different po…

The Anatomy of a Modular System for Media Content Analysis

Intelligent systems for the annotation of media content are increasingly being used for the automation of parts of social science research. In this domain the problem of integrating various Artificial Intelligence (AI) a…

A high-reproducibility and high-accuracy method for automated topic classification

Much of human knowledge sits in large databases of unstructured text. Leveraging this knowledge requires algorithms that extract and record metadata on unstructured text documents. Assigning topics to documents will enab…