DRr-Net: Dynamic Re-Read Network for Sentence Semantic Matching
نویسندگان
چکیده
منابع مشابه
Question Answering using Sentence Parsing and Semantic Network Matching
The paper describes a question answering system for German called InSicht. All documents in the system are analyzed by a syntactico-semantic parser in order to represent each document sentence by a semantic network (in the MultiNet formalism) or a partial semantic network (if only a parse in chunk mode succeeds). A question sent to InSicht is parsed yielding its semantic network representation ...
متن کاملLearning Semantic Concepts and Order for Image and Sentence Matching
Image and sentence matching has made great progress recently, but it remains challenging due to the large visualsemantic discrepancy. This mainly arises from that the representation of pixel-level image usually lacks of high-level semantic information as in its matched sentence. In this work, we propose a semantic-enhanced image and sentence matching model, which can improve the image represent...
متن کاملAn Improved Semantic Schema Matching Approach
Schema matching is a critical step in many applications, such as data warehouse loading, Online Analytical Process (OLAP), Data mining, semantic web [2] and schema integration. This task is defined for finding the semantic correspondences between elements of two schemas. Recently, schema matching has found considerable interest in both research and practice. In this paper, we present a new impr...
متن کاملMulti-Channel Pyramid Person Matching Network for Person Re-Identification
In this work, we present a Multi-Channel deep convolutional Pyramid Person Matching Network (MC-PPMN) based on the combination of the semantic-components and the colortexture distributions to address the problem of person reidentification. In particular, we learn separate deep representations for semantic-components and color-texture distributions from two person images and then employ pyramid ...
متن کاملPyramid Person Matching Network for Person Re-identification
In this work, we present a deep convolutional pyramid person matching network (PPMN) with specially designed Pyramid Matching Module to address the problem of person reidentification. The architecture takes a pair of RGB images as input, and outputs a similiarity value indicating whether the two input images represent the same person or not. Based on deep convolutional neural networks, our appr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Proceedings of the AAAI Conference on Artificial Intelligence
سال: 2019
ISSN: 2374-3468,2159-5399
DOI: 10.1609/aaai.v33i01.33017442