Imputing Missing Data Analysis in Web Service Quality Dataset for Improving QoS Prediction (Record no. 9962)
[ view plain ]
| 000 -LEADER | |
|---|---|
| fixed length control field | a |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20191104144907.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 191104b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | AIKTC-KRRC |
| Transcribing agency | AIKTC-KRRC |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 10304 |
| Author | Gaurav Raj |
| 245 ## - TITLE STATEMENT | |
| Title | Imputing Missing Data Analysis in Web Service Quality Dataset for Improving QoS Prediction |
| 250 ## - EDITION STATEMENT | |
| Volume, Issue number | Vol.6(2), May-Aug |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | New Delhi |
| Name of publisher, distributor, etc. | STM Journals |
| Year | 2019 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Pagination | 8-22p. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | The web services at present have countless options for similar tasks. This wide range in web services induce challenge to choose the best service among all available. QoS prediction is a key of the selection but it is very time-consuming affair. Any prediction strategy relies on accuracy and completeness of available data, especially in case of QOS Prediction. Feedback, throughput and response time are the major attribute that should not be missed and incorrect. So, it's important to identify the missing value in the web service datasets. Therefore, a study of three missing value prediction approaches was undertaken to investigate their performance for missing values in datasets for web service. Benchmarked WS Dream dataset include response time and throughput matrices of web services is selected to analyze the performance of selected approaches. An extensive experiment is performed, and results are collected, which conclude the superiority of MICE approach over other approaches. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| 9 (RLIN) | 4622 |
| Topical term or geographic name entry element | Computer Engineering |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 10305 |
| Co-Author | Mahajan, Manish |
| 773 0# - HOST ITEM ENTRY | |
| Place, publisher, and date of publication | Noida STM Journals |
| Title | Recent trends in programming languages |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| URL | http://computers.stmjournals.com/index.php?journal=RTPL&page=article&op=view&path%5B%5D=2278 |
| Link text | Click here |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Articles Abstract Database |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total Checkouts | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | School of Engineering & Technology | School of Engineering & Technology | Archieval Section | 04/11/2019 | 2020074 | 04/11/2019 | 04/11/2019 | Articles Abstract Database |