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150 Result(s)
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Chapter and Conference Paper
Out-of-Domain Semantics to the Rescue! Zero-Shot Hybrid Retrieval Models
The pre-trained language model (eg, BERT) based deep retrieval models achieved superior performance over lexical retrieval models (eg, BM25) in many passage retrieval tasks. However, limited work has been done to...
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Chapter and Conference Paper
Incorporating Complete Syntactical Knowledge for Spoken Language Understanding
Spoken Language Processing (SLU) is important in task-oriented dialog systems. Intent detection and slot filling are two significant tasks of SLU. State-of-the-art methods for SLU jointly solve these two tasks...
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Chapter and Conference Paper
CSDQA: Diagram Question Answering in Computer Science
Visual Question Answering (VQA) has been a research focus of the computer vision community for recent years. Most of them are accomplished and verified on images of natural scenes. However, Diagram Question An...
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Chapter and Conference Paper
A Recommender System with Advanced Time Series Medical Data Analysis for Diabetes Patients in a Telehealth Environment
Intelligent technologies are enjoying growing popularity in a telehealth environment for hel** improve the quality of chronic patients’ lives and provide better clinical decision-making to reduce the costs a...
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Chapter and Conference Paper
On Link Stability Detection for Online Social Networks
Link stability detection has been an important and long-standing problem within the link prediction domain. However, it has often been overlooked as being trivial and has not been adequately dealt with in link...
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Chapter and Conference Paper
Boost Clickbait Detection Based on User Behavior Analysis
Article in the web is usually titled with a misleading title to attract the users click for gaining click-through rate (CTR). A clickbait title may increase click-through rate, but decrease user experience. Th...
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Chapter and Conference Paper
Laser: Load-Adaptive Group Commit in Lock-Free Transaction Logging
Log manager is a key component of DBMS and is considered as the most prominent bottleneck in the modern in-memory OLTP system. In this paper, by addressing two existing performance hurdles in the current proce...
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Chapter and Conference Paper
Efficient Supervised Hashing via Exploring Local and Inner Data Structure
Recent years have witnessed the promising capacity of hashing techniques in tackling nearest neighbor search because of the high efficiency in storage and retrieval. Data-independent approaches (e.g., Locality...
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Chapter and Conference Paper
Quantitative Analysis of Learning Data in a Programming Course
Online learning platform, which has taken higher education by storm, provides an opportunity to track students’ learning behaviors. The vast majority of educational data mining research has been carried out ba...
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Chapter and Conference Paper
Precise Data Access on Distributed Log-Structured Merge-Tree
Log-structured merge tree decomposes a large database into multiple parts: an in-writing part and several read-only ones. It achieves high write throughput as well as low read latency. However, read requests h...
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Chapter and Conference Paper
Monte Carlo Based Incremental PageRank on Evolving Graphs
Computing PageRank for enormous and frequently evolving real-world network consumes sizable resource and comes with large computational overhead. To address this problem, IMCPR, an incremental PageRank algorit...
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Chapter and Conference Paper
Jointly Learning Attentions with Semantic Cross-Modal Correlation for Visual Question Answering
Visual Question Answering (VQA) has emerged as a prominent multi-discipline research problem in artificial intelligence. A number of recent studies are focusing on proposing attention mechanisms such as visual...
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Chapter and Conference Paper
A Learning Approach to Hierarchical Search Result Diversification
The queries in search engine that issued by users are often ambiguous. By returning diverse ranking results we can satisfy different information needs as far as possible. Recently, a hierarchical structure are...
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Chapter and Conference Paper
Extracting Clinical-event-packages from Billing Data for Clinical Pathway Mining
Clinical pathway can be used to reduce medical cost and improve medical efficiency. Traditionally, clinical pathways are designed by experts based on their experience. However, it is time consuming and sometim...
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Chapter and Conference Paper
Using Pull-Based Collaborative Development Model in Software Engineering Courses: A Case Study
The pull-based development model is an emerging way of contributing to distributed software projects within the Open Source Software (OSS) communities. To train students’ development skills with this modern pa...
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Chapter and Conference Paper
Finding Optimal Team for Multi-skill Task in Spatial Crowdsourcing
These days, Online To Offline (O2O) platforms have been develo** rapidly because of the popularization of smart phones and Mobile Internet. Spatial crowdsourcing, a burgeoning area in O2O market, is gaining ...
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Chapter and Conference Paper
Identifying the Academic Rising Stars via Pairwise Citation Increment Ranking
Predicting the fast-rising young researchers (the Academic Rising Stars) in the future provides useful guidance to the research community, e.g., offering competitive candidates to university for young faculty ...
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Chapter and Conference Paper
Mining Drug Properties for Decision Support in Dental Clinics
The rise of polypharmacy requires from health providers an awareness of a patient’s drug profile before prescribing. Existing methods to extract information on drug interactions do not integrate with the patie...
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Chapter and Conference Paper
Parallel Visual Assessment of Cluster Tendency on GPU
Determining the number of clusters in a data set is a critical issue in cluster analysis. The Visual Assessment of (cluster) Tendency (VAT) algorithm is an effective tool for investigating cluster tendency, wh...
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Chapter and Conference Paper
Deep Semantic Indexing Using Convolutional Localization Network with Region-Based Visual Attention for Image Database
In this paper, we introduce a novel deep semantic indexing method, a.k.a. captioning, for image database. Our method can automatically generate a natural language caption describing an image as a semantic refe...