Segmentation Driven Semantic Information Inference from 2.5D Data

Date

2009-01-01

Author

Bayramoglu, Neslihan
Alatan, Abdullah Aydın

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

48
views

0
downloads

In this work, we propose a multi-relational concept discovery method for business intelligence applications. Multi-relational data mining finds interesting patterns that span over multiple tables. The obtained patterns reveal useful information for decision making in business environments. However as the patterns include multiple relations, the search space gets intractably complex. In order to cope with this problem, various search strategies, heuristics and language pattern limitations are employed in multi-relational learning systems. In this work, we develop an ILP-based concept discovery method that uses inverse resolution for generalization of concept instances in the presence of background knowledge and refines these patterns into concept definitions by applying specialization operator There are two main benefits in this appoach. The first one is to relax the strong declarative biases and user-defined specifications. The second one is to integrate the method on relational databases so that usage of the system is facilitated in business intelligence applications.

Subject Keywords

Engineering, Computer science, Telecommunications, Engineering, Computer science

URI

https://hdl.handle.net/11511/37554

DOI

https://doi.org/10.1109/siu.2009.5136468

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

On-demand conversation customization for services in large smart environments Elgedawy, I. (IBM, 2011-01-01) Services in large smart environments, as defined in this paper, are "aware" of their users' contexts and goals and are able to automatically interact with one another in order to achieve these goals. Unfortunately, interactions between services (i.e., service conversations) are not necessarily compatible, as services could have different interfaces (i.e., signature incompatibilities), as well as different logic for message ordering (i.e., protocol incompatibilities). Such conversation incompatibilities crea...
Soft decoding of convolutional product codes on an FPGA platform Sanlı, Mustafa; Yılmaz, Ali Özgür; Department of Electrical and Electronics Engineering (2005) In today̕s world, high speed and accurate data transmission and storage is necessary in many fields of technology. The noise in the transmission channels and read-write errors occurring in the data storage devices cause data loss or slower data transmission. To solve these problems, the error rate of the received information must be minimized. Error correcting codes are used for detecting and correcting the errors. Turbo coding is an efficient error correction method which is commonly used in various commun...
Quantifying Uncertainty in Internet of Medical Things and Big-Data Services Using Intelligence and Deep Learning Al-Turjman, Fadi; Zahmatkesh, Hadi; Mostarda, Leonardo (Institute of Electrical and Electronics Engineers (IEEE), 2019-01-01) In the cloud-based Internet of Things (IoT) environments, quantifying uncertainty is an important element input to keep the acceptable level of reliability in various configurations. In this paper, we aim to address the pricing model of delivering data over the cloud while taking into consideration the dynamic uncertainty factors such as network topology, transmission/reception energy, nodal charge and power, and computation capacity. These uncertainty factors are mapped to different nodes with varying capa...
Providing Automated Actions in Wireless Multimedia Sensor Networks via Active Rules Oztarak, Hakan; Akkaya, Kemal; Yazıcı, Adnan (2011-09-28) Manual processing of multimedia data in Wireless Multimedia Sensor Networks (WMSNs) may not always be possible. This necessitates autonomous operation of data processing at the sink for taking actions as well as communicating with the appropriate personnel whenever needed. In this paper, we propose a framework for fusing and automated processing of incomplete/imprecise WMSN data using active rules. First, data fusion is performed via fuzzy logic to handle the uncertainty in the received data at the sink. We...
Energy efficient wireless unicast routing alternatives for machine-to-machine networks Tekbiyik, Neyre; Uysal, Elif (Elsevier BV, 2011-09-01) Machine-to-machine (M2M) communications is a new and rapidly developing technology for large-scale networking of devices without dependence on human interaction. Energy efficiency is one of the important design objectives for machine-to-machine network architectures that often contain multihop wireless subnetworks. Constructing energy-efficient routes for sending data through such networks is important not only for the longevity of the nodes which typically depend on battery energy, but also for achieving a...

Citation Formats

N. Bayramoglu and A. A. Alatan, “Segmentation Driven Semantic Information Inference from 2.5D Data,” 2009, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/37554.