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Xiu Li, Aron Henriksson, Martin Duneld, Jalal Nouri and Yongchao Wu
Educational content recommendation is a cornerstone of AI-enhanced learning. In particular, to facilitate navigating the diverse learning resources available on learning platforms, methods are needed for automatically linking learning materials, e.g., in...
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Marcos Orellana, Patricio Santiago García, Guillermo Daniel Ramon, Jorge Luis Zambrano-Martinez, Andrés Patiño-León, María Verónica Serrano and Priscila Cedillo
Health problems in older adults lead to situations where communication with peers, family and caregivers becomes challenging for seniors; therefore, it is necessary to use alternative methods to facilitate communication. In this context, Augmentative and...
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Isabella Gagliardi and Maria Teresa Artese
When integrating data from different sources, there are problems of synonymy, different languages, and concepts of different granularity. This paper proposes a simple yet effective approach to evaluate the semantic similarity of short texts, especially k...
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Somaiyeh Dehghan and Mehmet Fatih Amasyali
BERT, the most popular deep learning language model, has yielded breakthrough results in various NLP tasks. However, the semantic representation space learned by BERT has the property of anisotropy. Therefore, BERT needs to be fine-tuned for certain down...
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Youngki Park and Youhyun Shin
This paper presents a novel approach for finding the most semantically similar conversational sentences in Korean and English. Our method involves training separate embedding models for each language and using a hybrid algorithm that selects the appropri...
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Kirill Tyshchuk, Polina Karpikova, Andrew Spiridonov, Anastasiia Prutianova, Anton Razzhigaev and Alexander Panchenko
Embeddings, i.e., vector representations of objects, such as texts, images, or graphs, play a key role in deep learning methodologies nowadays. Prior research has shown the importance of analyzing the isotropy of textual embeddings for transformer-based ...
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Damião Ribeiro de Almeida, Cláudio de Souza Baptista and Fabio Gomes de Andrade
The use of location-based sensors has increased exponentially. Tracking moving objects has become increasingly common, consolidating a new field of research that focuses on trajectory data management. Such trajectories may be semantically enriched using ...
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Mohammad Daoud
Questions are crucial expressions in any language. Many Natural Language Processing (NLP) or Natural Language Understanding (NLU) applications, such as question-answering computer systems, automatic chatting apps (chatbots), digital virtual assistants, a...
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Shurong Sheng, Katrien Laenen, Luc Van Gool and Marie-Francine Moens
In this paper, we target the tasks of fine-grained image?text alignment and cross-modal retrieval in the cultural heritage domain as follows: (1) given an image fragment of an artwork, we retrieve the noun phrases that describe it; (2) given a noun phras...
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Huy Manh Nguyen, Tomo Miyazaki, Yoshihiro Sugaya and Shinichiro Omachi
Visual-semantic embedding aims to learn a joint embedding space where related video and sentence instances are located close to each other. Most existing methods put instances in a single embedding space. However, they struggle to embed instances due to ...
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