001454455 000__ 05531cam\a2200613\i\4500
001454455 001__ 1454455
001454455 003__ OCoLC
001454455 005__ 20230314003520.0
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001454455 007__ cr\cn\nnnunnun
001454455 008__ 230208s2023\\\\sz\a\\\\o\\\\\101\0\eng\d
001454455 020__ $$a9783031247552$$q(electronic bk.)
001454455 020__ $$a3031247558$$q(electronic bk.)
001454455 020__ $$z9783031247545
001454455 020__ $$z303124754X
001454455 0247_ $$a10.1007/978-3-031-24755-2$$2doi
001454455 035__ $$aSP(OCoLC)1369157835
001454455 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP
001454455 049__ $$aISEA
001454455 050_4 $$aZA3075
001454455 08204 $$a025.04$$223/eng/20230208
001454455 1112_ $$aCCIR (Conference)$$n(28th :$$d2022 :$$cChongqing, China).
001454455 24510 $$aInformation retrieval :$$b28th China Conference, CCIR 2022, Chongqing, China, September 16-18, 2022, revised selected papers /$$cYi Chang, Xiaofei Zhu (eds.).
001454455 24630 $$aCCIR 2022
001454455 264_1 $$aCham :$$bSpringer,$$c[2023]
001454455 264_4 $$c©2023
001454455 300__ $$a1 online resource (xi, 105 pages) :$$billustrations (chiefly color).
001454455 336__ $$atext$$btxt$$2rdacontent
001454455 337__ $$acomputer$$bc$$2rdamedia
001454455 338__ $$aonline resource$$bcr$$2rdacarrier
001454455 4901_ $$aLecture notes in computer science ;$$v13819
001454455 500__ $$aSelected conference proceedings.
001454455 500__ $$aIncludes author index.
001454455 5050_ $$aIntro -- Preface -- Organization -- Contents -- A Position-Aware Word-Level and Clause-Level Attention Network for Emotion Cause Recognition -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 The Definition of Emotion Cause Recognition -- 3.2 Position-Aware Word-Level and Clause-Level Attention Network for Emotion Cause Recognition -- 3.3 Model Training -- 4 Experiment -- 4.1 Experimental Settings -- 4.2 Experimental Results -- 4.3 Qualitative Analysis -- 5 Conclusion and Future Work -- References -- ID-Agnostic User Behavior Pre-training for Sequential Recommendation
001454455 5058_ $$a1 Introduction -- 2 Preliminaries -- 3 Methodology -- 3.1 ID-Agnostic User Behavior Pre-training -- 3.2 Fine-Tuning for Recommendation -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Experimental Results -- 5 Related Work -- 6 Conclusion -- References -- Enhance Performance of Ad-hoc Search via Prompt Learning -- 1 Introduction -- 2 Related Work -- 2.1 Ad Hoc Search with PTM -- 2.2 Prompt Learning -- 3 Preliminary -- 3.1 Ad hoc Search -- 3.2 Prompt Learning -- 4 Methodology -- 5 Experiments -- 5.1 Dataset and Metric -- 5.2 Experimental Setup -- 5.3 Result and Analysis -- 5.4 Case Study
001454455 5058_ $$a6 Conclusion -- References -- Syntax-Aware Transformer for Sentence Classification -- 1 Introduction -- 2 Syntax-Aware Transformer -- 2.1 Syntactic Subnetwork -- 2.2 Semantic Subnetwork -- 2.3 Merging Layer -- 3 Experiments -- 3.1 Datasets -- 3.2 Experimental Settings -- 3.3 Baseline Models -- 3.4 Results and Discussion -- 3.5 Case Study -- 4 Conclusions -- References -- Evaluation of Deep Reinforcement Learning Based Stock Trading -- 1 Introduction -- 2 Related Works -- 3 RL Modeling of Stock Trading -- 3.1 Problem Description -- 3.2 Mathematical Presentation -- 3.3 Trading Details
001454455 5058_ $$a3.4 Feasibility Analysis of RL-Based Stock Trading -- 4 Experiments -- 4.1 Stock Dataset -- 4.2 Methodology -- 4.3 Results -- 5 Conclusion and Future Works -- References -- InDNI: An Infection Time Independent Method for Diffusion Network Inference -- 1 Introduction -- 2 Related Work -- 3 Problem Statement -- 4 InDNI Algorithm -- 4.1 Node Representation Learning -- 4.2 Similarity Measure -- 4.3 Filtering Candidate Node Pairs -- 4.4 Network Inference -- 5 Experiments -- 5.1 Experimental Setup -- 5.2 Results and Discussion -- 6 Conclusion and Future Work -- References
001454455 5058_ $$aBeyond Precision: A Study on Recall of Initial Retrieval with Neural Representations -- 1 Introduction -- 2 Related Work -- 2.1 Initial Retrieval -- 2.2 Neural Representations for IR -- 3 Our Approach -- 3.1 Symbolic Index -- 3.2 Neural Index -- 3.3 Parallel Search Scheme -- 3.4 Sequential Search Scheme -- 3.5 Discussions -- 4 Experiments -- 4.1 Baselines and Experimental Settings -- 4.2 Evaluation Methodology -- 4.3 Retrieval Performance and Analysis -- 4.4 Analysis on Retrieved Relevant Documents -- 5 Conclusions -- References
001454455 506__ $$aAccess limited to authorized users.
001454455 520__ $$aThis book constitutes the refereed proceedings of the 28th China Conference on Information Retrieval, CCIR 2022, held in Chongqing, China, in September 2022. Information retrieval aims to meet the demand of human on the Internet to obtain information quickly and accurately. The 8 full papers presented were carefully reviewed and selected from numerous submissions. The papers provide a wide range of research results in information retrieval area.
001454455 588__ $$aDescription based on print version record.
001454455 650_0 $$aInformation retrieval$$vCongresses.
001454455 655_0 $$aElectronic books.
001454455 655_7 $$aConference papers and proceedings.$$2lcgft
001454455 7001_ $$aChang, Yi,$$eeditor.
001454455 7001_ $$aZhu, Xiaofei,$$eeditor.
001454455 77608 $$iPrint version:$$aCCIR (Conference) (28th : 2022 : Chongqing, China), creator.$$tInformation retrieval.$$dCham : Springer Nature Switzerland, 2023$$z9783031247545$$w(OCoLC)1359608339
001454455 830_0 $$aLecture notes in computer science ;$$v13819.
001454455 852__ $$bebk
001454455 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-24755-2$$zOnline Access$$91397441.1
001454455 909CO $$ooai:library.usi.edu:1454455$$pGLOBAL_SET
001454455 980__ $$aBIB
001454455 980__ $$aEBOOK
001454455 982__ $$aEbook
001454455 983__ $$aOnline
001454455 994__ $$a92$$bISE