Knowledge Science, Engineering and Management
13th International Conference, KSEM 2020, Hangzhou, China, August 28–30, 2020, Proceedings, Part I
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**u Tao
Computer Science
Data Mining and Knowledge Discovery
Database Management
Information Systems Applications (incl. Internet)
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Article
Open AccessFairness in graph-based semi-supervised learning
Machine learning is widely deployed in society, unleashing its power in a wide range of applications owing to the advent of big data. One emerging problem faced by machine learning is the discrimination from d...
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Chapter and Conference Paper
A Joint Framework for Explainable Recommendation with Knowledge Reasoning and Graph Representation
With the development of recommendation systems (RSs), researchers are no longer only satisfied with the recommendation results, but also put forward requirements for the recommendation reasons, which helps imp...
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Chapter and Conference Paper
Fast Fourier Orthogonalization over NTRU Lattices
FALCON is an efficient and compact lattice-based signature scheme. It is also one of the round 3 finalists in the NIST PQC standardization process. The core of FALCON is a trapdoor sampling algorithm, which ha...
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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
Tipster: A Topic-Guided Language Model for Topic-Aware Text Segmentation
The accurate segmentation and structural topics of plain documents not only meet people’s reading habit, but also facilitate various downstream tasks. Recently, some works have consistently given positive hint...
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Article
Simple Question Answering over Knowledge Graph Enhanced by Question Pattern Classification
Question answering over knowledge graph (KGQA), which automatically answers natural language questions by querying the facts in knowledge graph (KG), has drawn significant attention in recent years. In this pa...
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Article
On entropy-based term weighting schemes for text categorization
In text categorization, Vector Space Model (VSM) has been widely used for representing documents, in which a document is represented by a vector of terms. Since different terms contribute to a document’s seman...
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Article
Attentive multi-task learning for group itinerary recommendation
Tourism is one of the largest service industries and a popular leisure activity participated by people with friends or family. A significant problem faced by the tourists is how to plan sequences of points of ...
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Chapter and Conference Paper
Multi-label Feature Selection Algorithm via Maximizing Label Correlation-Aware Relevance and Minimizing Redundance with Mutation Binary Particle Swarm Optimization
Multi-label classification deals with a special supervised classification problem where any instance could be associated with multiple class labels simultaneously. As various applications emerge continuously i...
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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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Article
TAILOR: time-aware facility location recommendation based on massive trajectories
In traditional facility location recommendations, the objective is to select the best locations which maximize the coverage or convenience of users. However, since users’ behavioral habits are often influenced...
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Article
Label similarity-based weighted soft majority voting and pairing for crowdsourcing
Crowdsourcing services provide an efficient and relatively inexpensive approach to obtain substantial amounts of labeled data by employing crowd workers. It is obvious that the labeling qualities of crowd work...
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Article
Collaborative online ranking algorithms for multitask learning
There are many applications in which it is desirable to rank or order instances that belong to several different but related problems or tasks. Although unique, the individual ranking problem often shares char...
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Article
Semi-supervised multi-label feature learning via label enlarged discriminant analysis
Multi-label learning arises frequently in various domains including computer vision and machine learning and has attracted great interest in the last decades. However, current multi-label classification method...
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Book and Conference Proceedings
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Book and Conference Proceedings
Knowledge Science, Engineering and Management
13th International Conference, KSEM 2020, Hangzhou, China, August 28–30, 2020, Proceedings, Part II
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Chapter and Conference Paper
HEAM: Heterogeneous Network Embedding with Automatic Meta-path Construction
Heterogeneous information network (HIN) embedding is widely used in many real-world applications. Meta-path used in HINs can effectively extract semantic information among objects. However, the meta-path faces...
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Chapter and Conference Paper
Predicting Crowdsourcing Worker Performance with Knowledge Tracing
Knowledge-intensive crowdsourcing (KI-C) plays an important role in today’s knowledge economy. And competitive knowledge-intensive crowdsourcing (CKI-C) is a kind of KI-C in which tasks are released in the for...
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Chapter and Conference Paper
NovEA: A Novel Model of Entity Alignment Using Attribute Triples and Relation Triples
Entity alignment is the foundation of knowledge fusion, which can find the alignment relationships between entities in heterogeneous knowledge graphs. However, traditional methods rely on external information ...
