Explainable Semantic Communication for Text Tasks Article Swipe
Task-oriented semantic communication has gained increasing attention due to its ability to reduce the amount of transmitted data without sacrificing task performance. Although some prior efforts have been dedicated to developing semantic communications, the semantics in these works remains to be unexplainable. Challenges related to explainable semantic representation and knowledge-based semantic compression have yet to be explored. In this paper, we propose a triplet-based explainable semantic communication (TESC) scheme for representing text semantics efficiently. Specifically, we develop a semantic extraction method to convert text into triplets while using syntactic dependency analysis to enhance semantic completeness. Then, we design a semantic filtering method to further compress the duplicate and task-irrelevant triplets based on prior knowledge. The filtered triplets are encoded and transmitted to the receiver for completing intelligent tasks. Furthermore, we apply the propsed TESC scheme to two emblematic text tasks: sentiment analysis and question answering, in which the semantic codec is meticulously customized for each task. Experimental results demonstrate that 1) TESC scheme outperforms benchmarks in terms of Top-1 accuracy and transmission efficiency, and 2) TESC scheme enjoys about 150% performance gain compared to the traditional communication method.
Related Topics
Concepts
Computer science
Semantic computing
Semantic compression
Task (project management)
Semantics (computer science)
Natural language processing
Artificial intelligence
Semantic similarity
Semantic grid
Semantic integration
Semantic technology
Semantic Web
Economics
Programming language
Management
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2303.12286
- https://arxiv.org/pdf/2303.12286
- OA Status
- green
- Cited By
- 2
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4360829092
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4360829092Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2303.12286Digital Object Identifier
- Title
-
Explainable Semantic Communication for Text TasksWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-03-22Full publication date if available
- Authors
-
Chuanhong LiuList of authors in order
- Landing page
-
https://arxiv.org/abs/2303.12286Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2303.12286Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2303.12286Direct OA link when available
- Concepts
-
Computer science, Semantic computing, Semantic compression, Task (project management), Semantics (computer science), Natural language processing, Artificial intelligence, Semantic similarity, Semantic grid, Semantic integration, Semantic technology, Semantic Web, Economics, Programming language, ManagementTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 2Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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