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Social and Behavioral Sciences Commons™
Open Access. Powered by Scholars. Published by Universities.®
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- ArXiv (1)
- Computer science (1)
- Cross-border logistics (1)
- Data mining (1)
- Data model (1)
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- Data quality (1)
- Deduplication (1)
- Description and exchange of aggregations of Web resources (1)
- Document conflation (1)
- Document linking (1)
- GPS data (1)
- Hinterland transport (1)
- Motivation (1)
- OAI-ORE (1)
- Port congestion (1)
- Port of Colombo (1)
- Resource map (1)
- Scholarly big data (1)
- Scientific data (1)
- The Open Archives Initiative Object Reuse and Exchange (1)
Articles 1 - 4 of 4
Full-Text Articles in Social and Behavioral Sciences
Quantification Of Landside Congestion In Ports: An Analysis Based On Gps Data, Kumushini Thennakoon, Namal Bandaranayake, Senevi Kiridena, Asela K. Kulatunga
Quantification Of Landside Congestion In Ports: An Analysis Based On Gps Data, Kumushini Thennakoon, Namal Bandaranayake, Senevi Kiridena, Asela K. Kulatunga
Computer Science Faculty Publications
Hinterland transport is a critical segment in maritime cross-border logistics, which links the end-users of global supply chains to the maritime segment. Truck-based hinterland transport is known to cause congestion in and around ports. This study aimed to quantify the congestion caused by trucks at the Port of Colombo, which has not been a subject of a systematic study. To this end, the study makes use of GPS data. In addition to revealing heavy congestion within the port, the study also reveals significant variations in congestion during different times of the day with the duration of journeys peaking from 1200hrs …
Deeppatent2: A Large-Scale Benchmarking Corpus For Technical Drawing Understanding, Kehinde Ajayi, Xin Wei, Martin Gryder, Winston Shields, Jian Wu, Shawn M. Jones, Michal Kucer, Diane Oyen
Deeppatent2: A Large-Scale Benchmarking Corpus For Technical Drawing Understanding, Kehinde Ajayi, Xin Wei, Martin Gryder, Winston Shields, Jian Wu, Shawn M. Jones, Michal Kucer, Diane Oyen
Computer Science Faculty Publications
Recent advances in computer vision (CV) and natural language processing have been driven by exploiting big data on practical applications. However, these research fields are still limited by the sheer volume, versatility, and diversity of the available datasets. CV tasks, such as image captioning, which has primarily been carried out on natural images, still struggle to produce accurate and meaningful captions on sketched images often included in scientific and technical documents. The advancement of other tasks such as 3D reconstruction from 2D images requires larger datasets with multiple viewpoints. We introduce DeepPatent2, a large-scale dataset, providing more than 2.7 million …
Scholarly Big Data Quality Assessment: A Case Study Of Document Linking And Conflation With S2orc, Jian Wu, Ryan Hiltabrand, Dominik Soós, C. Lee Giles
Scholarly Big Data Quality Assessment: A Case Study Of Document Linking And Conflation With S2orc, Jian Wu, Ryan Hiltabrand, Dominik Soós, C. Lee Giles
Computer Science Faculty Publications
Recently, the Allen Institute for Artificial Intelligence released the Semantic Scholar Open Research Corpus (S2ORC), one of the largest open-access scholarly big datasets with more than 130 million scholarly paper records. S2ORC contains a significant portion of automatically generated metadata. The metadata quality could impact downstream tasks such as citation analysis, citation prediction, and link analysis. In this project, we assess the document linking quality and estimate the document conflation rate for the S2ORC dataset. Using semi-automatically curated ground truth corpora, we estimated that the overall document linking quality is high, with 92.6% of documents correctly linking to six major …
Object Reuse And Exchange, Michael L. Nelson, Carl Lagoze, Herbert Van De Sompel, Pete Johnston, Robert Sanderson, Simeon Warner, Jürgen Sieck (Ed.), Michael A. Herzog (Ed.)
Object Reuse And Exchange, Michael L. Nelson, Carl Lagoze, Herbert Van De Sompel, Pete Johnston, Robert Sanderson, Simeon Warner, Jürgen Sieck (Ed.), Michael A. Herzog (Ed.)
Computer Science Faculty Publications
The Open Archives Object Reuse and Exchange (OAI-ORE) project defines standards for the description and exchange of aggregations of Web resources. The OAI-ORE abstract data model is conformant with the Architecture of the World Wide Web and leverages concepts from the Semantic Web, including RDF descriptions and Linked Data. In this paper we provide a brief review of a motivating example and its serialization in Atom.