4,176 Result(s)
within
Chapter
Conference Paper
Ke** Zhang
Information Storage and Retrieval
Information Systems Applications (incl. Internet)
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Chapter and Conference Paper
Evaluation of Deep Reinforcement Learning Based Stock Trading
Stock is one of the most important targets in investment. However, it is challenging to manually design a profitable strategy in the highly dynamic and complex stock market. Modern portfolio management usually...
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Chapter and Conference Paper
Syntax-Aware Transformer for Sentence Classification
Sentence classification is a significant task in natural language processing (NLP) and is applied in many fields. The syntactic and semantic properties of words and phrases often determine the success of sente...
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Chapter and Conference Paper
Enhance Performance of Ad-hoc Search via Prompt Learning
Recently, pre-trained language models (PTM) have achieved great success on ad hoc search. However, the performance decline in low-resource scenarios demonstrates the capability of PTM has not been inspired ful...
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Chapter and Conference Paper
Beyond Precision: A Study on Recall of Initial Retrieval with Neural Representations
Vocabulary mismatch is a central problem in information retrieval (IR), i.e., the relevant documents may not contain the same (symbolic) terms of the query. Recently, neural representations have shown great su...
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Chapter and Conference Paper
Contrastive Deep Knowledge Tracing
Knowledge tracing (KT) aims to predict student performance on the next question according to historical records. Recently deep learning-based models for KT task successfully modeling student responses receive ...
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Chapter and Conference Paper
Extreme Multi-label Classification with Hierarchical Multi-task for Product Attribute Identification
Identification of product attributes (product type, brand, color, gender, etc.) from a query is critically important for e-commerce search systems, especially the identification of brand intent. Recently, Name...
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Chapter and Conference Paper
Research on Depth-Adaptive Dual-Arm Collaborative Gras** Method
Among the existing dual-arm cooperative gras** methods, the dual-arm cooperative gras** method based on RGB camera is the mainstream intelligent method. However, these methods often require predefined dept...
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Chapter and Conference Paper
DHA: Product Title Generation with Discriminative Hierarchical Attention for E-commerce
Product titles play an important role in E-Commerce sites. However, manually crafting product titles needs tremendous time and human effort. It is expected that product titles can be automatically generated, b...
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Chapter and Conference Paper
Managing Learners’ Memory Strength in a POMDP-Based Learning Path Recommender System
This paper views the learning path recommendation task as a sequential decision problem and considers Partially Observable Markov Decision Process (POMDP) as an adequate approach. This work proposes M-POMDP, a...
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Chapter and Conference Paper
Anti-Clone: A Lightweight Approach for RFID Cloning Attacks Detection
Millions of radio frequency identification (RFID) tags are pervasively used all around the globe to identify a wide variety of objects inexpensively. However, the tag cannot use energy-hungry cryptography due ...
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Chapter and Conference Paper
Temporal Event Reasoning Using Multi-source Auxiliary Learning Objectives
Temporal event reasoning is vital in modern information-driven applications operating on news articles, social media, financial reports, etc. Recent works train deep neural nets to infer temporal events and re...
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Chapter and Conference Paper
A Model Driven Approach to Transform Business Vision-Oriented Decision-Making Requirement into Solution-Oriented Optimization Model
Currently in our highly connected society, there is a strong requirement for decision-makers in organizations to coordinate and schedule their activities. Frequently, there are various uncertain factors, multi...
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Chapter and Conference Paper
ToothCR: A Two-Stage Completion and Reconstruction Approach on 3D Dental Model
Deep neural networks have made a number of achievements both in tooth segmentation and arrangement on complete 3D dental models. But few studies have used deep learning methods on the tooth completion and reco...
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Chapter and Conference Paper
Leveraging Customer Reviews for E-commerce Query Generation
Customer reviews are an effective source of information about what people deem important in products (e.g. “strong zipper” for tents). These crowd-created descriptors not only highlight key product attributes,...
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Chapter and Conference Paper
Parallel High Utility Itemset Mining
Association rule mining is a popular data mining task for finding relationships between values from the itemsets that co-occur frequently in a transactional database. Association rule mining has many applicati...
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Chapter and Conference Paper
An Oriented Attention Model for Infectious Disease Cases Prediction
Effective infectious disease prediction supports the success of infection prevention and control. Several attention-based predictive models can be applied to undertake the prediction task. However, using a sin...
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Chapter and Conference Paper
Ultra-short-Term Load Forecasting Model Based on VMD and TGCN-GRU
Load forecasting is to use historical load information to estimate the load demand for a period of time in the future. At present, mode decomposition algorithm is often used in the field to improve the forecas...
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Chapter and Conference Paper
Squeezing Water from a Stone: A Bag of Tricks for Further Improving Cross-Encoder Effectiveness for Reranking
While much recent work has demonstrated that hard negative mining can be used to train better bi-encoder models, few have considered it in the context of cross-encoders, which are key ingredients in modern re...
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Chapter and Conference Paper
A Novel Risk Assessment Method Based on Hybrid Algorithm for SCADA
With the frequent occurrence of cyber attacks in recent years, cyber attacks have become a major factor affecting the security and reliability of power SCADA. We urgently need an effective SCADA risk assessmen...
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Chapter and Conference Paper
Two-Stage Traffic Clustering Based on HNSW
Traffic flow clustering is a common task to analyze urban traffic using GPS data of urban vehicles. Existing density-based traffic flow clustering methods generally have two important problems, that is to not ...
