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- research-articleOctober 2024
Dialogue act-based partner persona extraction for consistent personalized response generation
Expert Systems with Applications: An International Journal (EXWA), Volume 254, Issue Chttps://doi.org/10.1016/j.eswa.2024.124380AbstractThe ability of a dialogue model to keep not being out of context during a conversation, so-called keeping the consistency, has long been a critical issue in generating more human-like personalized responses. However, most of the previous works ...
Highlights- Existing dialogue agents generate responses not consistent with their partners.
- To generate a partner-consistent response, persona extraction is an essential task.
- Dialogue act is an attribute that conveys the intent of the ...
- research-articleAugust 2024
Embedding Two-View Knowledge Graphs with Class Inheritance and Structural Similarity
KDD '24: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data MiningPages 3931–3941https://doi.org/10.1145/3637528.3671941Numerous large-scale knowledge graphs (KGs) fundamentally represent two-view KGs: an ontology-view KG with abstract classes in ontology and an instance-view KG with specific collections of entities instantiated from ontology classes. Two-view KG ...
- research-articleNovember 2023
Cross-modal contrastive learning for aspect-based recommendation
AbstractKnowledge-enhanced recommender systems with aspects have improved recommendation performance by better profiling user preferences. Existing models can be divided into graph-based and text-based depending on the type of external knowledge: ...
Highlights- Integrate multimodal data (knowledge graph and review text) for aspect-based recommendation.
- Propose a novel cross-modal contrastive learning with the correlation between multimodal data.
- Learn informative de-biased aspect-level ...
- research-articleOctober 2023
Active learning for cross-sentence n-ary relation extraction
Information Sciences: an International Journal (ISCI), Volume 645, Issue Chttps://doi.org/10.1016/j.ins.2023.119328AbstractN-ary relation extraction models are required to be trained on large amount of high-quality data, but it is challenging to obtain such data in effect; thus, models are forced to rely on a limited amount of low-quality labeled data. ...
- research-articleApril 2023
Confident Action Decision via Hierarchical Policy Learning for Conversational Recommendation
WWW '23: Proceedings of the ACM Web Conference 2023Pages 1386–1395https://doi.org/10.1145/3543507.3583536Conversational recommender systems (CRS) aim to acquire a user’s dynamic interests for a successful recommendation. By asking about his/her preferences, CRS explore current needs of a user and recommend items of interest. However, previous works may not ...
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- research-articleMarch 2022
Open-world knowledge graph completion for unseen entities and relations via attentive feature aggregation
Information Sciences: an International Journal (ISCI), Volume 586, Issue CPages 468–484https://doi.org/10.1016/j.ins.2021.11.085AbstractMost of knowledge graph completion (KGC) models are designed for static KGs where entity and relation sets are fixed. These approaches are inherently transductive because they simply predict the plausibility of facts whose entities and ...
- research-articleDecember 2021
Multi-task learning for spatial events prediction from social data
Information Sciences: an International Journal (ISCI), Volume 581, Issue CPages 278–290https://doi.org/10.1016/j.ins.2021.09.049Highlights- The method predicts the subtypes of events in a specific location.
- Two-level ...
Multi-task learning is becoming more popular and is being applied in a variety of applications. It improves the accuracy of prediction by simultaneously learning related tasks and saves cost through shared structures. In particular, ...
- research-articleOctober 2021
DORIC: discovering topological relations based on spatial link composition
Knowledge and Information Systems (KAIS), Volume 63, Issue 10Pages 2645–2669https://doi.org/10.1007/s10115-021-01603-2AbstractWith the proliferation of the Semantic Web technologies, more and more spatial knowledge bases are being published on the Web. Discovering spatial links among spatial knowledge bases is crucial in achieving real-time applications such as reasoning ...
- research-articleOctober 2020
Cross-sentence N-ary Relation Extraction using Entity Link and Discourse Relation
CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge ManagementPages 705–714https://doi.org/10.1145/3340531.3412011This paper presents an efficient method of extracting n-ary relations from multiple sentences which is called Entity-path and Discourse relation-centric Relation Extractor (EDCRE). Unlike previous approaches, the proposed method focuses on an entity ...
- research-articleOctober 2020
News Recommendation with Topic-Enriched Knowledge Graphs
CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge ManagementPages 695–704https://doi.org/10.1145/3340531.3411932News recommendation systems? purpose is to tackle the immense amount of news and offer personalized recommendations to users. A major issue in news recommendation is to capture the precise news representations for the efficacy of recommended items. ...
- research-articleOctober 2020
Designing an integrated knowledge graph for smart energy services
The Journal of Supercomputing (JSCO), Volume 76, Issue 10Pages 8058–8085https://doi.org/10.1007/s11227-018-2672-3AbstractThe sharp growth of distributed energy-related resources requires an efficient energy management for future grids. The traditional power grid that highly depends on information model standards collects energy data depending on them and creates ...
- research-articleMay 2020
Efficient generation of spatiotemporal relationships from spatial data streams and static data
Information Processing and Management: an International Journal (IPRM), Volume 57, Issue 3https://doi.org/10.1016/j.ipm.2020.102205Highlights- Define three types of spatiotemporal relationships (SRs).
- Design a novel ...
Recently, a massive amount of position-annotated data is being generated in a stream fashion. Also, massive amounts of static data including spatial features are collected and made available. In the Internet of Things (IoT) ...
- research-articleNovember 2019
Learning Region Similarity over Spatial Knowledge Graphs with Hierarchical Types and Semantic Relations
CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge ManagementPages 669–678https://doi.org/10.1145/3357384.3358008A large number of spatial knowledge graphs (SKGs) are available from spatially enriched knowledge bases, e.g., DBpedia and YAGO2. This provides a great chance to understand valuable information about the regions surrounding us. However, it is hard to ...
- research-articleMay 2019
Predicate constraints based question answering over knowledge graph
Information Processing and Management: an International Journal (IPRM), Volume 56, Issue 3Pages 445–462https://doi.org/10.1016/j.ipm.2018.12.003AbstractGenerally, QA systems suffer from the structural difference where a question is composed of unstructured data, while its answer is made up of structured data in a Knowledge Graph (KG). To bridge this gap, most approaches use lexicons ...
- articleApril 2019
Reliable TF-based recommender system for capturing complex correlations among contexts
Journal of Intelligent Information Systems (JIIS), Volume 52, Issue 2Pages 337–365https://doi.org/10.1007/s10844-018-0514-7Context-aware recommender systems (CARS) exploit multiple contexts to improve user experience in embracing new information and services. Tensor factorization (TF), a type of latent factor model, has achieved remarkable performance in CARS. TF learns ...
- articleMarch 2019
SECoG: semantically enhanced mashup of CoAP-based IoT services
Service Oriented Computing and Applications (SPSOCA), Volume 13, Issue 1Pages 81–94https://doi.org/10.1007/s11761-019-00254-0One of the noticeable characteristics of the Internet-of-Things (IoT) devices is that they are resource-constrained, which makes them incompatible with the standard Internet protocols, e.g., HTTP. Nevertheless, IoT offers the Constrained Application ...
- research-articleOctober 2018
Knowledge Graph Completion by Context-Aware Convolutional Learning with Multi-Hop Neighborhoods
CIKM '18: Proceedings of the 27th ACM International Conference on Information and Knowledge ManagementPages 257–266https://doi.org/10.1145/3269206.3271769The main focus of relational learning for knowledge graph completion (KGC) lies in exploiting rich contextual information for facts. Many state-of-the-art models incorporate fact sequences, entity types, and even textual information. Unfortunately, most ...
- research-articleFebruary 2018
Enabling smart objects discovery via constructing hypergraphs of heterogeneous IoT interactions
Journal of Information Science (JIPP), Volume 44, Issue 1Pages 110–124https://doi.org/10.1177/0165551516674164Recent advances in the Internet of Things IoT have led to the rise of a new paradigm: Social Internet of Things SIoT. However, the new paradigm, as inspired by the idea that smart objects will soon have a certain degree of social consciousness, is still ...
- research-articleDecember 2017
An adaptive plan-based approach to integrating semantic streams with remote RDF data
Journal of Information Science (JIPP), Volume 43, Issue 6Pages 852–865https://doi.org/10.1177/0165551516670278To satisfy a user's complex requirements, Resource Description Framework RDF Stream Processing RSP systems envision the fusion of remote RDF data with semantic streams, using common data models to query semantic streams continuously. While streaming ...
- articleDecember 2017
A fast and scalable approach for IoT service selection based on a physical service model
Information Systems Frontiers (KLU-ISFI), Volume 19, Issue 6Pages 1357–1372https://doi.org/10.1007/s10796-016-9650-1Information Systems (ISs) have become one of the crucial tools for various organizations in managing and coordinating business processes. Now we are entering the era of the Internet of Things (IoT). IoT is a paradigm in which real-world physical things ...