Improving code search with co-attentive representation learning
Searching and reusing existing code from a large-scale codebase, eg, GitHub, can help
developers complete a programming task efficiently. Recently, Gu et al. proposed a deep …
developers complete a programming task efficiently. Recently, Gu et al. proposed a deep …
Two-stage attention-based model for code search with textual and structural features
Searching and reusing existing code from a large scale codebase can largely improve
developers' programming efficiency. To support code reuse, early code search models …
developers' programming efficiency. To support code reuse, early code search models …
Recurrent neural network based collaborative filtering for QoS prediction in IoV
As the emerging paradigm that is believed to be conducive to the development of intelligent
transportation systems (ITS), Internet of Vehicles (IoV) is constructed with a number of …
transportation systems (ITS), Internet of Vehicles (IoV) is constructed with a number of …
Caesar: context-aware explanation based on supervised attention for service recommendations
Explainable recommendations have drawn more attention from both academia and industry
recently, because they can help users better understand recommendations (ie, why some …
recently, because they can help users better understand recommendations (ie, why some …
Fine-grained co-attentive representation learning for semantic code search
Code search aims to find code snippets from large-scale code repositories based on the
developer's query intent. A significant challenge for code search is the semantic gap …
developer's query intent. A significant challenge for code search is the semantic gap …
Context-aware cross feature attentive network for click-through rate predictions
S Lee, S Hwang - Applied Intelligence, 2024 - Springer
Click-through rate (CTR) prediction aims to estimate the likelihood that a user will interact
with an item. It has gained significant attention in areas such as online advertising and e …
with an item. It has gained significant attention in areas such as online advertising and e …
A crowd-sourcing recommendation algorithm OPCA-CF using outer-product co-attention mechanism
K Bi, J Liu, Q Zhao, Y Chen, B Xing… - … Testing and Evaluation, 2024 - Taylor & Francis
With the rapid development of information technology, crowd-sourcing technology is
increasingly used in non-invasive monitoring in smart cities. Applying recommendation …
increasingly used in non-invasive monitoring in smart cities. Applying recommendation …
CUTE: A Collaborative Fusion Representation-Based Fine-Tuning and Retrieval Framework for Code Search
Q Song, J Liu, H Hu - International Conference on Collaborative …, 2023 - Springer
Code search aims at searching semantically related code snippets from the large-scale
database based on a given natural descriptive query. Fine-tuning pre-trained models for …
database based on a given natural descriptive query. Fine-tuning pre-trained models for …
Property Recommendation System With Geospatial Data Analytics Andnatural Language Processing For Urban Land Use
SK Riehl - 2020 - engagedscholarship.csuohio.edu
Abstract Recently Cuyahoga County has been tremendously improved as properties are
being constructed, renovated, or altered for new land use transactions on a nearly daily …
being constructed, renovated, or altered for new land use transactions on a nearly daily …
[引用][C] 항목의순서와부가정보를반영한BERT 기반의순차적추천시스템
조수아， 김영신， 고희원， 장은조， 유사라… - 한국정보과학회학술 …, 2023 - dbpia.co.kr
순차적 추천 시스템 (Sequential Recommendation System) 은 사용자의 이전 상호작용 항목을
기반으로사용자의 선호도를 파악하고 앞으로의 상호작용을 추천하는 중요한 기술로, 다양한 …
기반으로사용자의 선호도를 파악하고 앞으로의 상호작용을 추천하는 중요한 기술로, 다양한 …