A Hypothesis Testing-based Framework for Software Cross-modal Retrieval in Heterogeneous Semantic Spaces
Abstract
References
Index Terms
- A Hypothesis Testing-based Framework for Software Cross-modal Retrieval in Heterogeneous Semantic Spaces
Recommendations
Multi-modal attention network learning for semantic source code retrieval
ASE '19: Proceedings of the 34th IEEE/ACM International Conference on Automated Software EngineeringCode retrieval techniques and tools have been playing a key role in facilitating software developers to retrieve existing code fragments from available open-source repositories given a user query (e.g., a short natural language text describing the ...
Testing the cluster hypothesis in distributed information retrieval
How to merge and organise query results retrieved from different resources is one of the key issues in distributed information retrieval. Some previous research and experiments suggest that cluster-based document browsing is more effective than a single ...
A semantic model for cross-modal and multi-modal retrieval
ICMR '13: Proceedings of the 3rd ACM conference on International conference on multimedia retrievalIn this paper, a semantic model for cross-modal and multi-modal retrieval is studied. We assume that the semantic correlation of multimedia data from different modalities can be depicted in a probabilistic generation framework. Media data from different ...
Comments
Information & Contributors
Information
Published In
![cover image ACM Transactions on Software Engineering and Methodology](/cms/asset/2b448187-ea52-4cf0-ace4-83ad6751014d/3610417.cover.jpg)
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Author Tags
Qualifiers
- Research-article
Funding Sources
- National Natural Science Foundation of China
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 282Total Downloads
- Downloads (Last 12 months)212
- Downloads (Last 6 weeks)2
Other Metrics
Citations
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in