488 Result(s)
within
Computer Science
Information Storage and Retrieval
Information Systems Applications (incl. Internet)
**u Tao
Chapter
Conference Paper
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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 Feature Labeling into Crowdsourcing for More Accurate Aggregation Labels
Crowdsourcing is a popular way of collecting crowd wisdom and has been deployed in various senarios. Effective answer collection and answer aggregation are two important crowdsourcing topics as workers may give 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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Chapter and Conference Paper
SPAN: Subgraph Prediction Attention Network for Dynamic Graphs
This paper proposes a novel model for predicting subgraphs in dynamic graphs, an extension of traditional link prediction. This proposed end-to-end model learns a map** from the subgraph structures in the cu...
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Chapter and Conference Paper
A Stepwise Path Selection Scheme Based on Multiple QoS Parameters Evaluation in SDN
Nowadays, the best-effort service can not guarantee the quality of service (QoS) for all kinds of services. QoS routing is an important method to guarantee QoS requirements. It involves path selection for flow...
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Chapter and Conference Paper
Difficulty-Controllable Visual Question Generation
Visual Question Generation (VQG) aims to generate questions from images. Existing studies on this topic focus on generating questions solely based on images while neglecting the difficulty of questions. Howeve...
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Chapter and Conference Paper
Learning Cooperative Max-Pressure Control by Leveraging Downstream Intersections Information for Traffic Signal Control
Traffic signal control problems are critical in urban intersections. Recently, deep reinforcement learning demonstrates impressive performance in the control of traffic signals. The design of state and reward ...
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Chapter and Conference Paper
Generating Pseudo Connectives with MLMs for Implicit Discourse Relation Recognition
Due to the lack of connectives, the recognition of implicit discourse relations faces a big challenge. An early attempt overcomes this difficulty by predicting connectives with the use of the statistical langu...
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Chapter and Conference Paper
Topology Self-optimization for Anti-tracking Network via Nodes Distributed Computing
Anti-tracking network aims to protect the privacy of network users’ identities and communication relationship. The research of P2P-based anti-tracking network has attracted more and more attentions because of ...
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Chapter and Conference Paper
Self-supervised Learning for Semantic Sentence Matching with Dense Transformer Inference Network
Semantic sentence matching concerns predicting the relationship between a pair of natural language sentences. Recently, many methods based on interaction structure have been proposed, usually involving encoder...
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Chapter and Conference Paper
Learning Modality-Invariant Features by Cross-Modality Adversarial Network for Visual Question Answering
Visual Question Answering (VQA) is a typical multimodal task with significant development prospect on web application. In order to answer the question based on the corresponding image, a VQA model needs to utiliz...
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Chapter and Conference Paper
Construction of Chinese Pediatric Medical Knowledge Graph
The knowledge graph is a promising method for knowledge management in the big data era. Pediatrics, as an essential branch of clinical medicine, has accumulated a large amount of medical data. This paper appli...
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Chapter and Conference Paper
Generating Short Product Descriptors Based on Very Little Training Data
We propose a pipeline model for summarising a short textual product description for inclusion in an online advertisement banner. While a standard approach is to truncate the advertiser’s original product descr...
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Chapter and Conference Paper
Near-Duplicate Video Retrieval Through Toeplitz Kernel Partial Least Squares
The existence of huge volumes of near-duplicate videos shows a rising demand on effective near-duplicate video retrieval technique in copyright violation and search result re-ranking. In this paper, Kernel Par...
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Chapter and Conference Paper
Research on Fine-Grained Sentiment Classification
Aiming at the fine-grained sentiment classification that distinguishes the emotional intensity, the commonly used dataset SST-1 is analyzed in depth. Through the analysis, it is found that the dataset has ser...
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Chapter and Conference Paper
Classification over Clustering: Augmenting Text Representation with Clusters Helps!
Considering that words with different characteristic in the text have different importance for classification, grou** them together separately can strengthen the semantic expression of each part. Thus we pro...
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Chapter and Conference Paper
Domain Information Enhanced Dependency Parser
Dependency parsing has been an important task in the natural language processing (NLP) community. Supervised methods have achieved great success these years. However, these models can suffer significant perfor...
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Chapter and Conference Paper
Mining User Profiles from Query Log
This paper introduces a novel method for mining user profiles (e.g., age, gender) using the query log in a search engine. The proposed method combines the advantage of the neural network for representation le...
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Chapter and Conference Paper
Learning Relational Fractals for Deep Knowledge Graph Embedding in Online Social Networks
Knowledge Graphs (KGs) have deep and impactful applications in a wide-array of information networks such as natural language processing, recommendation systems, predictive analysis, recognition, classificatio...
