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Full-Text Articles in Computer Engineering
Table Headers: An Entrance To The Data Mine, George Nagy, Sharad C. Seth
Table Headers: An Entrance To The Data Mine, George Nagy, Sharad C. Seth
CSE Conference and Workshop Papers
Algorithmic methods are demonstrated for information extraction from table header elements, including data categories and data hierarchies. The table headers are found with the Minimum Index Point Search algorithm. The header-path alignment and header completion algorithms yield database-ready table content and configuration statistics on a random sample of 400 diverse tables with ground truth and 1120 tables without ground truth from international statistical data sites.
Impacts Of Soil Type And Moisture On The Capacity Of Multi-Carrier Modulation In Internet Of Underground Things, Abdul Salam, Mehmet C. Vuran
Impacts Of Soil Type And Moisture On The Capacity Of Multi-Carrier Modulation In Internet Of Underground Things, Abdul Salam, Mehmet C. Vuran
CSE Conference and Workshop Papers
Unique interactions between soil and communication components in wireless underground communications necessitate revisiting fundamental communication concepts from a different perspective. In this paper, capacity profile of wireless underground (UG) channel for multi-carrier transmission techniques is analyzed based on empirical antenna return loss and channel frequency response models in different soil types and moisture values. It is shown that data rates in excess of 124 Mbps are possible for distances up to 12 m. For shorter distances and lower soil moisture conditions, data rates of 362 Mbps can be achieved. It is also shown that due to soil moisture variations, UG …
Learning Hierarchically Decomposable Concepts With Active Over-Labeling, Yuji Mo, Stephen Scott, Doug Downey
Learning Hierarchically Decomposable Concepts With Active Over-Labeling, Yuji Mo, Stephen Scott, Doug Downey
CSE Conference and Workshop Papers
Many classification tasks target high-level concepts that can be decomposed into a hierarchy of finer-grained subconcepts. For example, some string entities that are Locations are also Attractions, some Attractions are Museums, etc. Such hierarchies are common in named entity recognition (NER), document classification, and biological sequence analysis. We present a new approach for learning hierarchically decomposable concepts. The approach learns a high-level classifier (e.g., location vs. non-location) by seperately learning multiple finer-grained classifiers (e.g., museum vs. non-museum), and then combining the results. Soliciting labels at a finer level of granularity than that of the target concept is a new approach …