TTCS$^\mathcalE$: a Vectorial Resource for Computing Conceptual Similarity
In this paper we introduce the TTCS$^{\mathcal{E}}$, a linguistic resource that relies on BabelNet, NASARI and ConceptNet, that has now been used to compute the conceptual similarity between concept pairs. The conceptual representation herein provides uniform access to concepts based on BabelNet synset IDs, and consists of a vector-based semantic representation which is compliant with the Conceptual Spaces, a geometric framework for common-sense knowledge representation and reasoning. The TTCS$^{\mathcal{E}}$ has been evaluated in a preliminary experimentation on a conceptual similarity task.
Code (0)
등록된 구현이 없습니다.
Tasks
Common Sense ReasoningSimilar Papers 제목 키워드 기반
MERALI at SemEval-2017 Task 2 Subtask 1: a Cognitively Inspired approach
In this paper we report on the participation of the MERALI system to the SemEval Task 2 Subtask 1. The MERALI system approaches conceptual similarity through a simple, cognitively inspired, heuristics; it builds on a lin…
Common Sense ReasoningTask 2TTCS: Test-Time Curriculum Synthesis for Self-Evolving
Test-Time Training offers a promising way to improve the reasoning ability of large language models (LLMs) by adapting the model using only the test questions. However, existing methods struggle with difficult reasoning …
Learning-driven Zero Trust in Distributed Computing Continuum Systems
Converging Zero Trust (ZT) with learning techniques can solve various operational and security challenges in Distributed Computing Continuum Systems (DCCS). Implementing centralized ZT architecture is seen as unsuitable …
Decision MakingDistributed ComputingManagementRepresentation LearningMeasuring anomalies in cigarette sales by using official data from Spanish provinces: Are there only the anomalies detected by the Empty Pack Surveys (EPS) used by Transnational Tobacco Companies (TTCs)?
There is literature that questions the veracity of the studies commissioned by the transnational tobacco companies (TTC) to measure the illicit tobacco trade. Furthermore, there are studies that indicate that the Empty P…
Adaptive Parallel Monte Carlo Tree Search for Efficient Test-time Compute Scaling
Monte Carlo Tree Search (MCTS) is an effective test-time compute scaling (TTCS) method for improving the reasoning performance of large language models, but its highly variable execution time leads to severe long-tail la…