The ?rst SKLOIS Conference on informationsecurity and Cryptography(CISC 2005) was organized by the State keylaboratory of informationsecurity of the Chinese Academy of Sciences. It was held in Beijing, China, Decem...
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ISBN:
(数字)9783540324249
ISBN:
(纸本)9783540308553
The ?rst SKLOIS Conference on informationsecurity and Cryptography(CISC 2005) was organized by the State keylaboratory of informationsecurity of the Chinese Academy of Sciences. It was held in Beijing, China, December 15-17,2005andwassponsoredbytheInstituteofSoftware,theChineseAcademy of Sciences, the Graduate School of the Chinese Academy of Sciences and the National Science Foundation of China. The conference proceedings, represe- ing invited and contributed papers, are published in this volume of Springer’s Lecture Notes in computer Science (LNCS) series. The area of research covered by CISC has been gaining importance in recent years, and a lot of fundamental, experimental and applied work has been done, advancing the state of the art. The program of CISC 2005 covered numerous ?elds of research within the general scope of the conference. The International Program Committee of the conference received a total of 196 submissions (from 21 countries). Thirty-three submissions were selected for presentation as regular papers and are part of this volume. In addition to this track, the conference also hosted a short-paper track of 32 presentations that were carefully selected as well. All submissions were reviewed by experts in the relevant areas and based on their ranking and strict selection criteria the papers were selected for the various tracks. We note that stricter criteria were applied to papers co-authored by program committee members. We further note that, obviously, no member took part in in?uencing the ranking of his or her own submissions.
Non-overlapping Cross-domain Sequential Recommendation (NCSR) is the task that focuses on domain knowledge transfer without overlapping entities. Compared with traditional Cross-domain Sequential Recommendation (CSR),...
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Non-overlapping Cross-domain Sequential Recommendation (NCSR) is the task that focuses on domain knowledge transfer without overlapping entities. Compared with traditional Cross-domain Sequential Recommendation (CSR), NCSR poses several challenges: 1) NCSR methods often rely on explicit item IDs, overlooking semantic information among entities. 2) Existing CSR mainly relies on domain alignment for knowledge transfer, risking semantic loss during alignment. 3) Most previous studies do not consider the many-to-one characteristic, which is challenging because of the utilization of multiple source domains. Given the above challenges, we introduce the prompt learning technique for Many-to-one Non-overlapping Cross-domain Sequential Recommendation (MNCSR) and propose a Text-enhanced Co-attention Prompt Learning Paradigm (TCPLP). Specifically, we capture semantic meanings by representing items through text rather than IDs, leveraging natural language universality to facilitate cross-domain knowledge transfer. Unlike prior works that need to conduct domain alignment, we directly learn transferable domain information, where two types of prompts, i.e., domain-shared and domain-specific prompts, are devised, with a co-attention-based network for prompt encoding. Then, we develop a two-stage learning strategy, i.e., pre-train & prompt-tuning paradigm, for domain knowledge pre-learning and transferring, respectively. We conduct extensive experiments on three datasets and the experimental results demonstrate the superiority of our TCPLP. Our source codes have been publicly released.
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