A survey analysis on duplicate detection in Hierarchical Data

2015 ◽  
Author(s):  
Shital Gaikwad ◽  
Nagaraju Bogiri
Keyword(s):  
Hierarchical Data ◽  
Survey Analysis ◽  
Duplicate Detection

Efficient and Effective Duplicate Detection in Hierarchical Data

2020 ◽  
Vol 17 (8) ◽  
pp. 3548-3552
Author(s):  
M. S. Roobini ◽  
P. B. S. Sumanth Kumar ◽  
P. B. Raviteja Reddy ◽  
Anitha Ponraj ◽  
J. Aruna
Keyword(s):  
High Accuracy ◽  
Cutting Edge ◽  
Hierarchical Data ◽  
Copy Detection ◽  
Bayesian Algorithm ◽  
Social Data ◽  
Xml Data ◽  
Duplicate Detection ◽  
Novel Technique

Although there is a long profession on distinguishing duplicates, just a handful in social data arrangements center around copy detection in ever more complex progressive systems, including XML data. Right now, present a novel technique for XML duplicate discovery, Renamed XMLDup. XMLDup utilizes a Bayesian algorithm defining the chance of duplicating two XML components, taking into account the data within the components, but also how data is structured. Likewise, to improve the effectiveness of Unit Review, Novel technique for pruning, equipped for noteworthy increases over the un-streamlined calculation rule, is introduced. We demonstrate through trials that our estimate is can accomplish high accuracy via trials we show our estimation is outflanking another cutting-edge duplicate discovery arrangement, both as far as proficiency and of adequacy.

scholarly journals Efficient and Effective Duplicate Detection in Hierarchical Data

2013 ◽  
Vol 25 (5) ◽  
pp. 1028-1041 ◽  
Author(s):  
L. Leitão ◽  
P. Calado ◽  
M. Herschel
Keyword(s):  
Hierarchical Data ◽  
Duplicate Detection

Awareness Analysis of Smart Car Parking System in Heterogeneous High Density Clusters

2017 ◽  
Vol DC CPS 2017 (01) ◽  
pp. 22-26 ◽  
Author(s):  
Elsie Chidinma Anderson ◽  
A. A. Obayi ◽  
K.C. Okafor
Keyword(s):  
Traffic Congestion ◽  
Urban Population ◽  
New Technology ◽  
Innovative Technology ◽  
Survey Analysis ◽  
Metropolitan Cities ◽  
Port Harcourt ◽  
Parking System ◽  
Statistical Survey ◽  
Co Emission

The swiftly growing urban population of Nigeria is generating lots of tension in the cities in line with the rapid increase of vehicles. This is due to hitherto reliance on the present parking system which has no standard to check for parking spaces, hence generating problems such as traffic congestion, time wastage in search of parking slot, fuel consumption/CO emission, insecurity of vehicles etc. This work presents a quantitative statistical survey analysis conducted in selected metropolitan cities in Port Harcourt, Nigeria. The aim is to create awareness on Smart Car Parking System (SCPS) for heterogeneous clustered environments. The results of the conducted analysis showed that the awareness of this innovative technology is still at its tender stage in Nigeria. Findings shows that people are willing to adopt this new technology to assist in overcoming the challenges faced in the present parking system that is unstructured. A brief description of proposed SCPS based on Big data hardware is presented.

Students’ meaningful learning experiences from participating in organic chemistry writing-to-learn activities

2021 ◽  
Author(s):  
Trisha Gupte ◽  
Field M. Watts ◽  
Jennifer A. Schmidt-McCormack ◽  
Ina Zaimi ◽  
Anne Ruggles Gere ◽  
...  
Keyword(s):  
Organic Chemistry ◽  
Learning Strategies ◽  
Learning Experience ◽  
Learning Experiences ◽  
Meaningful Learning ◽  
Writing To Learn ◽  
Chemistry Laboratory ◽  
Primary Data ◽  
Survey Analysis ◽  
Problem Solving Skills

Teaching organic chemistry requires supporting learning strategies that meaningfully engage students with the challenging concepts and advanced problem-solving skills needed to be successful. Such meaningful learning experiences should encourage students to actively choose to incorporate new concepts into their existing knowledge frameworks by appealing to the cognitive, affective, and psychomotor domains of learning. This study provides a qualitative analysis of students’ meaningful learning experiences after completing three Writing-to-Learn (WTL) assignments in an organic chemistry laboratory course. The assignments were designed to appeal to the three domains necessary for a meaningful learning experience, and this research seeks to understand if and how the WTL assignments promoted students’ meaningful learning. The primary data collected were the students’ responses to open-ended feedback surveys conducted after each assignment. These responses were qualitatively analyzed to identify themes across students’ experiences about their meaningful learning. The feedback survey analysis was triangulated with interviews conducted after each assignment. The results identify how the assignments connected to students’ existing knowledge from other courses and indicate that assignment components such as authentic contexts, clear expectations, and peer review supported students’ meaningful learning experiences. These results inform how assignment design can influence students’ learning experiences and suggest implications for how to support students’ meaningful learning of organic chemistry through writing.

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