Match!
Information Processing and Management
IF
3.89
Papers
4354
Papers 4289
1 page of 429 pages (4,289 results)
Newest
#1Xiaoling Gu (Hangzhou Dianzi University)
#2Fei Gao (Hangzhou Dianzi University)
Last. Pai Peng (Tencent)
view all 4 authors...
Abstract As handling fashion big data with Artificial Intelligence (AI) has become exciting challenges for computer scientists, fashion studies have received increasing attention in computer vision, machine learning and multimedia communities in the past few years. In this paper, introduce the progress in fashion research and provide a taxonomy of these fashion studies that include low-level fashion recognition, middle-level fashion understanding and high-level fashion applications. Finally, we ...
Source
#1Mladen Russo (University of Split)H-Index: 8
#2Luka Kraljevic (University of Split)H-Index: 1
Last. Marjan Sikora (University of Split)H-Index: 4
view all 4 authors...
Abstract Identifying perceived emotional content of music constitutes an important aspect of easy and efficient search, retrieval, and management of the media. One of the most promising use cases of music organization is an emotion-based playlist, where automatic music emotion recognition plays a significant role in providing emotion related information, which is otherwise, generally unavailable. Based on the importance of the auditory system in emotional recognition and processing, in this stud...
Source
#1Weiming Lu (ZJU: Zhejiang University)H-Index: 10
#2Peng Wang (ZJU: Zhejiang University)
Last. Chen Chen (ZJU: Zhejiang University)
view all 5 authors...
Abstract The task of enriching cross-lingual links is to find articles in different languages but representing the same real-world object between multilingual Wikis. In this paper, we propose a novel M ulti- M odal S emantic M atching approach, called MMSM, to enrich cross-lingual links for online Wikis. Specifically, MMSM jointly trains two novel end-to-end neural matching models, Entity Description Matching Model and Entity Image Matching Model, which can utilize entity description and images ...
Source
#1Wenhui Li (TJU: Tianjin University)H-Index: 2
#2Shu Xiang (TJU: Tianjin University)H-Index: 1
Last. Tong Hao (Tianjin Normal University)H-Index: 9
view all 7 authors...
Abstract With the widespread application of 3D capture devices, diverse 3D object datasets from different domains have emerged recently. Consequently, how to obtain the 3D objects from different domains is becoming a significant and challenging task. The existing approaches mainly focus on the task of retrieval from the identical dataset, which significantly constrains their implementation in real-world applications. This paper addresses the cross-domain object retrieval in an unsupervised manne...
Source
#1Zhulin Tao (CUC: Communication University of China)
#2Yinwei WeiH-Index: 1
Last. Tat-Seng Chua (NUS: National University of Singapore)H-Index: 65
view all 6 authors...
Abstract Graph neural networks (GNNs) have shown great potential for personalized recommendation. At the core is to reorganize interaction data as a user-item bipartite graph and exploit high-order connectivity among user and item nodes to enrich their representations. While achieving great success, most existing works consider interaction graph based only on ID information, foregoing item contents from multiple modalities (e.g., visual, acoustic, and textual features of micro-video items). Dist...
Source
#1Xi-jun He (Beijing University of Technology)H-Index: 2
#2Xue Meng (Beijing University of Technology)
Last. Ting Pang (Information Technology University)
view all 5 authors...
Abstract We calculated the matching values of technology supply and demand texts based on texts semantic similarity with Word2Vec and Cosine similarity algorithms, and then proposed a new index named Supply-Demand Matching Efficiency (SDME) to measure the matching efficiency of online technology trading platforms (OTTPs). Through the empirical research on the three types of OTTPs, the findings are as follows: First, the SDME of Zhejiang Market (Government-Owned, Government-Operated, GOGO), Techn...
Source
Abstract In the online health community, the doctor-patient interaction is one of the most important functional modules. A large volume of unstructured text data has been generated in the doctor-patient interaction process. This development is worth exploring. In this paper, we mainly explore the influences of online doctor-patient interaction content on patient satisfaction. We collected the online doctor-patient interaction text data from a big online health community ( http://haodf.com ) in C...
Source
#1Shalini Jangra (IITR: Indian Institute of Technology Roorkee)
#2Durga Toshniwal (IITR: Indian Institute of Technology Roorkee)H-Index: 5
Abstract Collaborative frequent itemset mining involves analyzing the data shared from multiple business entities to find interesting patterns from it. However, this comes at the cost of high privacy risk. Because some of these patterns may contain business-sensitive information and hence are denoted as sensitive patterns. The revelation of such patterns can disclose confidential information. Privacy-preserving data mining (PPDM) includes various sensitive pattern hiding (SPH) techniques, which ...
Source
#1Lidia Ogiela (Pedagogical University of Kraków)H-Index: 1
Abstract This paper will present a new computing methodology based on the application of cognitive information systems in transformative computing tasks. This methodology is an innovative approach to the tasks of transformative computing, which – based on the techniques of collection of data obtained from various sources and registered by means of various sensors – serve the purpose of their appropriate classification. Enhancing the here-discussed techniques by aspects of their semantic descript...
Source
#2Vitor Basto-Fernandes (ISCTE-IUL: ISCTE – University Institute of Lisbon)H-Index: 7
view all 5 authors...
Abstract In recent years, most content-based spam filters have been implemented using Machine Learning (ML) approaches by means of token-based representations of textual contents. After introducing multiple performance enhancements, the impact has been virtually irrelevant. Recent studies have introduced synset-based content representations as a reliable way to improve classification, as well as different forms to take advantage of semantic information to address problems, such as dimensionality...
Source
12345678910
Top fields of study
Data mining
World Wide Web
Library science
Information system
Information retrieval
Computer science