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Previous work of ours on Semantic Storytelling uses text analytics procedures including Named Entity Recognition and Event Detection. In this paper, we outline our longer-term vision on Semantic Storytelling and describe the current…

Sentence embedding methods offer a powerful approach for working with short textual constructs or sequences of words. By representing sentences as dense numerical vectors, many natural language processing (NLP) applications have improved…

Computation and Language · Computer Science 2021-10-05 Yuan An , Alexander Kalinowski , Jane Greenberg

Few-shot named entity recognition (NER) aims to recognize novel named entities in low-resource domains utilizing existing knowledge. However, the present few-shot NER models assume that the labeled data are all clean without noise or…

Computation and Language · Computer Science 2023-12-14 Xiaojun Xue , Chunxia Zhang , Tianxiang Xu , Zhendong Niu

The short text has been the prevalent format for information of Internet in recent decades, especially with the development of online social media, whose millions of users generate a vast number of short messages everyday. Although…

Computation and Language · Computer Science 2014-12-18 Yuan Zuo , Jichang Zhao , Ke Xu

Languages shared by people differ in different regions based on their accents, pronunciation and word usages. In this era sharing of language takes place mainly through social media and blogs. Every second swing of such a micro posts exist…

Computation and Language · Computer Science 2018-04-13 Barathi Ganesh HB

Topic detection is a challenging task, especially without knowing the exact number of topics. In this paper, we present a novel approach based on neural network to detect topics in the micro-blogging dataset. We use an unsupervised neural…

Information Retrieval · Computer Science 2020-06-18 Cong Wan , Shan Jiang , Cuirong Wang , Cong Wang , Changming Xu , Xianxia Chen , Ying Yuan

Relation extraction is essentially a text classification problem, which can be tackled by fine-tuning a pre-trained language model (LM). However, a key challenge arises from the fact that relation extraction cannot straightforwardly be…

Computation and Language · Computer Science 2024-10-03 Frank Mtumbuka , Steven Schockaert

Text-based person search aims to retrieve images of a certain pedestrian by a textual description. The key challenge of this task is to eliminate the inter-modality gap and achieve the feature alignment across modalities. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2021-12-14 Shiping Li , Min Cao , Min Zhang

Entity Linking (EL) is the process of associating ambiguous textual mentions to specific entities in a knowledge base. Traditional EL methods heavily rely on large datasets to enhance their performance, a dependency that becomes problematic…

Computation and Language · Computer Science 2024-10-11 Xukai Liu , Ye Liu , Kai Zhang , Kehang Wang , Qi Liu , Enhong Chen

User-generated texts available on the web and social platforms are often long and semantically challenging, making them difficult to annotate. Obtaining human annotation becomes increasingly difficult as problem domains become more…

Computation and Language · Computer Science 2023-09-19 Joseph Gatto , Sarah M. Preum

The prevalence of social media has made information sharing possible across the globe. The downside, unfortunately, is the wide spread of misinformation. Methods applied in most previous rumor classifiers give an equal weight, or attention,…

Social and Information Networks · Computer Science 2019-10-04 Sansiri Tarnpradab , Kien A. Hua

Automation of humor detection and rating has interesting use cases in modern technologies, such as humanoid robots, chatbots, and virtual assistants. In this paper, we propose a novel approach for detecting and rating humor in short texts…

Computation and Language · Computer Science 2024-03-20 Issa Annamoradnejad , Gohar Zoghi

Segmenting text into semantically coherent segments is an important task with applications in information retrieval and text summarization. Developing accurate topical segmentation requires the availability of training data with ground…

Computation and Language · Computer Science 2019-04-16 Saurav Manchanda , George Karypis

To disclose overlapped multiple relations from a sentence still keeps challenging. Most current works in terms of neural models inconveniently assuming that each sentence is explicitly mapped to a relation label, cannot handle multiple…

Computation and Language · Computer Science 2018-11-13 Xinsong Zhang , Pengshuai Li , Weijia Jia , Hai Zhao

In this paper, we study the problem of author identification under double-blind review setting, which is to identify potential authors given information of an anonymized paper. Different from existing approaches that rely heavily on feature…

Machine Learning · Computer Science 2016-12-20 Ting Chen , Yizhou Sun

Being able to automatically discover synonymous entities in an open-world setting benefits various tasks such as entity disambiguation or knowledge graph canonicalization. Existing works either only utilize entity features, or rely on…

Computation and Language · Computer Science 2020-05-12 Chenwei Zhang , Yaliang Li , Nan Du , Wei Fan , Philip S. Yu

Network data enriched with textual information, referred to as text networks, arise in a wide range of applications, including email communications, scientific collaborations, and legal contracts. In such settings, both the structure of…

Methodology · Statistics 2025-05-09 Maoyu Zhang , Biao Cai , Dong Li , Xiaoyue Niu , Jingfei Zhang

When developers investigate a new bug report, they search for similar previously fixed bug reports and discussion threads attached to them. These discussion threads convey important information about the behavior of the bug including…

Software Engineering · Computer Science 2021-05-26 Rrezarta Krasniqi

The authorship attribution is a problem of considerable practical and technical interest. Several methods have been designed to infer the authorship of disputed documents in multiple contexts. While traditional statistical methods based…

Computation and Language · Computer Science 2018-03-28 Jeaneth Machicao , Edilson A. Corrêa , Gisele H. B. Miranda , Diego R. Amancio , Odemir M. Bruno

The task of automatic language identification (LID) involving multiple dialects of the same language family in the presence of noise is a challenging problem. In these scenarios, the identity of the language/dialect may be reliably present…

Audio and Speech Processing · Electrical Eng. & Systems 2020-04-06 Bharat Padi , Anand Mohan , Sriram Ganapathy