Knowledge Science, Engineering and Management
Home > Computing and Information Technology > Computer science > Artificial intelligence > Knowledge Science, Engineering and Management: 13th International Conference, KSEM 2020, Hangzhou, China, August 28–30, 2020, Proceedings, Part I(12274 Lecture Notes in Computer Science)
Knowledge Science, Engineering and Management: 13th International Conference, KSEM 2020, Hangzhou, China, August 28–30, 2020, Proceedings, Part I(12274 Lecture Notes in Computer Science)

Knowledge Science, Engineering and Management: 13th International Conference, KSEM 2020, Hangzhou, China, August 28–30, 2020, Proceedings, Part I(12274 Lecture Notes in Computer Science)

|
     0     
5
4
3
2
1




Available


About the Book

This two-volume set of LNAI 12274 and LNAI 12275 constitutes the refereed proceedings of the 13th International Conference on Knowledge Science, Engineering and Management, KSEM 2020, held in Hangzhou, China, in August 2020.*The 58 revised full papers and 27 short papers were carefully reviewed and selected from 291 submissions. The papers of the first volume are organized in the following topical sections: knowledge graph; knowledge representation; knowledge management for education; knowledge-based systems; and data processing and mining. The papers of the second volume are organized in the following topical sections: machine learning; recommendation algorithms and systems; social knowledge analysis and management; text mining and document analysis; and deep learning. *The conference was held virtually due to the COVID-19 pandemic.

Table of Contents:
Knowledge Graph.- Event-centric Tourism Knowledge Graph — A Case Study of Hainan.- Extracting Short Entity Descriptions for Open-World Extension to Knowledge Graph Completion Models.- Graph Embedding Based on Characteristic of Rooted Subgraph Structure.- Knowledge Graphs Meet Geometry for Semi-supervised Monocular Depth Estimation.- Topological Graph Representation Learning on Property Graph.- Measuring Triplet Trustworthiness in Knowledge Graphs via Expanded Relation Detection.- A Contextualized Entity Representation for Knowledge Graph Completion.- A Dual Fusion Model for Attributed Network Embedding.- Attention-based Knowledge Tracing with Heterogeneous Information Network Embedding.- Knowledge Representation.- Detecting Statistically Significant Events in Large Heterogeneous Attribute Graphs via Densest Subgraphs.- Edge Features Enhanced Graph Attention Network for Relation Extraction.- MMEA: Entity Alignment for Multi-Modal Knowledge Graph.- A Hybrid Model with Pre-trained Entity-Aware Transformer for Relation Extraction.- NovEA: A Novel Model of Entity Alignment Using Attribute Triples and Relation Triples.- A Robust Representation with Pre-Trained Start and End Characters Vectors for Noisy Word Recognition.- Intention Multiple-representation Model for Logistics Intelligent Customer Service.- Identifying Loners from Their Project Collaboration Records – A Graph-based Approach.- Node Embedding over Attributed Bipartite Graphs.- FastLogSim: A quick log pattern parser scheme based on text similarity.- Knowledge Management for Education.- Robotic Pushing and Grasping Knowledge Learning via Attention Deep Q-Learning Network.- A Dynamic Answering Path based Fusion Model for KGQA.- Improving Deep Item-based Collaborative Filtering with Bayesian Personalized Ranking for MOOC Course Recommendation.- Online Programming Education Modeling and Knowledge Tracing.- Enhancing Pre-Trained Language Models by Self-Supervised Learning for Story Cloze Test.- MOOCRec: An Attention Meta-path Based Model for Top-K Recommendation in MOOC.- Knowledge-based Systems.- PVFNet: Point-view fusion network for 3D shape recognition.- HEAM: Heterogeneous Network Embedding with Automatic Meta-path Construction.- A Graph Attentive Network Model for P2P Lending Fraud Detection.- An Empirical Study on Recent Graph Database Systems.- Bibliometric Analysis of Twitter Knowledge management publications related to Health Promotion.- Automatic cerebral artery system labeling using registration and key points tracking.- Page-level handwritten word spotting via discriminative feature learning.- NADSR: A Network Anomaly Detection Scheme based on Representation.- A Knowledge-based Scheduling Method for Multi-Satellite Range System.- IM-Net: Semantic Segmentation Algorithm for Medical Images Based on Mutual Information Maximization.- Data Processing and Mining.- Fast Backward Iterative Laplacian Score for Unsupervised Feature Selection.- Improving Low-Resource Chinese Event Detection with Multi-Task Learning.- Feature Selection Using Sparse Twin Support Vector Machine with correntropy-induces loss.- Customized Decision Tree for Fat Multi-resolution Chart Patterns Classification.- Predicting user influence in the propagation of toxic information.- Extracting Distinctive Shapelets with Random Selection for Early Classification.- Butterfly-Based Higher-Order Clustering on Bipartite Networks.- Learning Dynamic Pricing Rules for Flight Tickets.


Best Sellers


Product Details
  • ISBN-13: 9783030551292
  • Publisher: Springer Nature Switzerland AG
  • Publisher Imprint: Springer Nature Switzerland AG
  • Height: 235 mm
  • No of Pages: 510
  • Returnable: Y
  • Series Title: 12274 Lecture Notes in Computer Science
  • Width: 155 mm
  • ISBN-10: 3030551296
  • Publisher Date: 02 Aug 2020
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Series Title: 12274 Lecture Notes in Computer Science
  • Sub Title: 13th International Conference, KSEM 2020, Hangzhou, China, August 28–30, 2020, Proceedings, Part I


Similar Products

Add Photo
Add Photo

Customer Reviews

REVIEWS      0     
Click Here To Be The First to Review this Product
Knowledge Science, Engineering and Management: 13th International Conference, KSEM 2020, Hangzhou, China, August 28–30, 2020, Proceedings, Part I(12274 Lecture Notes in Computer Science)
Springer Nature Switzerland AG -
Knowledge Science, Engineering and Management: 13th International Conference, KSEM 2020, Hangzhou, China, August 28–30, 2020, Proceedings, Part I(12274 Lecture Notes in Computer Science)
Writing guidlines
We want to publish your review, so please:
  • keep your review on the product. Review's that defame author's character will be rejected.
  • Keep your review focused on the product.
  • Avoid writing about customer service. contact us instead if you have issue requiring immediate attention.
  • Refrain from mentioning competitors or the specific price you paid for the product.
  • Do not include any personally identifiable information, such as full names.

Knowledge Science, Engineering and Management: 13th International Conference, KSEM 2020, Hangzhou, China, August 28–30, 2020, Proceedings, Part I(12274 Lecture Notes in Computer Science)

Required fields are marked with *

Review Title*
Review
    Add Photo Add up to 6 photos
    Would you recommend this product to a friend?
    Tag this Book Read more
    Does your review contain spoilers?
    What type of reader best describes you?
    I agree to the terms & conditions
    You may receive emails regarding this submission. Any emails will include the ability to opt-out of future communications.

    CUSTOMER RATINGS AND REVIEWS AND QUESTIONS AND ANSWERS TERMS OF USE

    These Terms of Use govern your conduct associated with the Customer Ratings and Reviews and/or Questions and Answers service offered by Bookswagon (the "CRR Service").


    By submitting any content to Bookswagon, you guarantee that:
    • You are the sole author and owner of the intellectual property rights in the content;
    • All "moral rights" that you may have in such content have been voluntarily waived by you;
    • All content that you post is accurate;
    • You are at least 13 years old;
    • Use of the content you supply does not violate these Terms of Use and will not cause injury to any person or entity.
    You further agree that you may not submit any content:
    • That is known by you to be false, inaccurate or misleading;
    • That infringes any third party's copyright, patent, trademark, trade secret or other proprietary rights or rights of publicity or privacy;
    • That violates any law, statute, ordinance or regulation (including, but not limited to, those governing, consumer protection, unfair competition, anti-discrimination or false advertising);
    • That is, or may reasonably be considered to be, defamatory, libelous, hateful, racially or religiously biased or offensive, unlawfully threatening or unlawfully harassing to any individual, partnership or corporation;
    • For which you were compensated or granted any consideration by any unapproved third party;
    • That includes any information that references other websites, addresses, email addresses, contact information or phone numbers;
    • That contains any computer viruses, worms or other potentially damaging computer programs or files.
    You agree to indemnify and hold Bookswagon (and its officers, directors, agents, subsidiaries, joint ventures, employees and third-party service providers, including but not limited to Bazaarvoice, Inc.), harmless from all claims, demands, and damages (actual and consequential) of every kind and nature, known and unknown including reasonable attorneys' fees, arising out of a breach of your representations and warranties set forth above, or your violation of any law or the rights of a third party.


    For any content that you submit, you grant Bookswagon a perpetual, irrevocable, royalty-free, transferable right and license to use, copy, modify, delete in its entirety, adapt, publish, translate, create derivative works from and/or sell, transfer, and/or distribute such content and/or incorporate such content into any form, medium or technology throughout the world without compensation to you. Additionally,  Bookswagon may transfer or share any personal information that you submit with its third-party service providers, including but not limited to Bazaarvoice, Inc. in accordance with  Privacy Policy


    All content that you submit may be used at Bookswagon's sole discretion. Bookswagon reserves the right to change, condense, withhold publication, remove or delete any content on Bookswagon's website that Bookswagon deems, in its sole discretion, to violate the content guidelines or any other provision of these Terms of Use.  Bookswagon does not guarantee that you will have any recourse through Bookswagon to edit or delete any content you have submitted. Ratings and written comments are generally posted within two to four business days. However, Bookswagon reserves the right to remove or to refuse to post any submission to the extent authorized by law. You acknowledge that you, not Bookswagon, are responsible for the contents of your submission. None of the content that you submit shall be subject to any obligation of confidence on the part of Bookswagon, its agents, subsidiaries, affiliates, partners or third party service providers (including but not limited to Bazaarvoice, Inc.)and their respective directors, officers and employees.

    Accept

    New Arrivals

    Inspired by your browsing history


    Your review has been submitted!

    You've already reviewed this product!