Short texts
Quality biased Ranking of Short Texts in Microblogging Services
... In this paper, we focus on predicting the quality of very short texts which are obtained from Twit- ter. Twitter is a free social networking and micro- blogging service that enables its users to send and ...
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Intelligent mining for Disease Prediction using Short Texts
... Rosario et al. [2] introduced the Machine Learning (ML) Approach for Identifying Disease-Treatment Relations in Short Texts The main focus of their work is on entity recognition for diseases and treatments. ...
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Convolutional Neural Networks for Authorship Attribution of Short Texts
... ods that dealt with AA of short text. However, we were able to find research in AA using tra- ditional as well as related approaches. Character and word n-grams have been used as the core of many authorship ...
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A Recurrent and Compositional Model for Personality Trait Recognition from Short Texts
... exploring short texts. Typically, classification of such texts tends to be particularly challenging for state-of-the-art BoW based approaches due, in part, to the noisy nature of such data (Han and ...
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QurSim: A corpus for evaluation of relatedness in short texts
... language short texts has many interesting application such as: words sense disambiguation, information extraction and retrieval, automatic indexing, lexical selection, text summarization, automatic ...
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Predicting Sentiment of Polish Language Short Texts
... The goal of this paper is to use all available Polish language data sets to seek the best possible performance in supervised senti- ment analysis of short texts. We use text collections with labeled ...
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Name List Only? Target Entity Disambiguation in Short Texts
... The assumptions resemble the main insight of MentionRank except the co-mention (multiple en- tities occur in one document). Co-mention sel- dom happens in short texts, and can be treated as the same because ...
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Deep Convolutional Neural Networks for Sentiment Analysis of Short Texts
... for short text messages (Go et ...of short texts such as single sentences and and microblogging posts, like Twitter messages, is challenging because of the limited amount of contextual data in this ...
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Unsupervised Topic Modeling for Short Texts Using Distributed Representations of Words
... gregating short messages), our approach works on the entire corpus ...of short texts by directly modeling unordered word-pair co-occurrences (biterms) over the ...
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A Fast Approach for Semantic Similar Short Texts Retrieval
... rent short texts similarity measurement techniques could not handle when the data collection size be- comes ...similar texts which is rather difficult to determine by ...
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Short Texts Analasisby Using Semantic Enrichment and Hashing
... Clustering short texts by their meaning is a challenging ...two texts have similar meanings, we only need to check if they have similar ...on texts represented by word-count vectors (bag- ...
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Generalizing Unmasking for Short Texts
... where texts are attributed to a set of given authors, recently, authorship verifica- tion has been proposed as a more fundamental ...long texts, unmasking by Koppel and Schler (2004) has since been ...
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Parallel Discourse Annotations on a Corpus of Short Texts
... The RST annotations have been created according to the guidelines (Stede, 2016) that were developed for the Pots- dam Commentary Corpus (Stede and Neumann, 2014, in German). The relation set is quite close to the origi- ...
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Combination of Convolutional and Recurrent Neural Network for Sentiment Analysis of Short Texts
... In this paper, we present a jointed CNN and RNN architecture that takes the local features extracted by CNN as input to RNN for sentiment analysis of short texts. We develop an end-to-end and bottom-up ...
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Extended Feature Spaces Based Classifier Ensembles for Sentiment Analysis of Short Texts
... of short texts by extending fea- ture ...of short texts because of the size limitation of express- ing ideas on social networks such as ...for short sentiment classification on ...
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Using Short Texts to Teach English as Second Language: An Integrated Approach
... using short texts and how to use them to train learners in varied language and literary skills among those who read and learn English language as a Second ...longer texts are useful, they should be ...
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Hashing and Enriching Short Texts Query Search Engine through Semantic Signals
... converts texts into compact binary codes using deep neural networks ...convert texts from a high dimensional vectors into a low- dimension binary vectors, and meantime the semantic relationship between ...
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Clusters Merging Method for Short Texts Clustering
... volume short texts clustering problems produced by mobile ...of short texts of volume data and dynamic growth, whose time complexity is O(N 2 ...large-scale short texts ...
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Towards segment based recognition of argumentation structure in short texts
... Naive annotators: In (Peldszus and Stede, 2013b), we presented an agreement study with 26 naive and untrained annotators: undergradu- ate students in a “class-room annotation” szenario, where task introduction, guideline ...
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