Retrieval Result Presentation and Evaluation

2010 ◽  
pp. 125-136 ◽  
Author(s):  
Shengli Wu ◽  
Yaxin Bi ◽  
Xiaoqin Zeng
Keyword(s):  
Retrieval Result

scholarly journals A Comparison of Retrieval Result Relevance Judgments Between American and Chinese Users

2020 ◽  
Vol 28 (3) ◽  
pp. 148-168
Author(s):  
Jin Zhang ◽  
Yuehua Zhao ◽  
Xin Cai ◽  
Taowen Le ◽  
Wei Fei ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Relevance Judgment ◽  
Search Tasks ◽  
Retrieval Systems ◽  
Relevance Judgments ◽  
Cross Language Information Retrieval ◽  
Subject Categories ◽  
Information Retrieval Systems ◽  
Retrieval Result ◽  
Cross Language

Relevance judgment plays an extremely significant role in information retrieval. This study investigates the differences between American users and Chinese users in relevance judgment during the information retrieval process. 384 sets of relevance scores with 50 scores in each set were collected from 16 American users and 16 Chinese users as they judged retrieval records from two major search engines based on 24 predefined search tasks from 4 domain categories. Statistical analyses reveal that there are significant differences between American assessors and Chinese assessors in relevance judgments. Significant gender differences also appear within both the American and the Chinese assessor groups. The study also revealed significant interactions among cultures, genders, and subject categories. These findings can enhance the understanding of cultural impact on information retrieval and can assist in the design of effective cross-language information retrieval systems.

Comparison of Two Methods of Solving Electromagnetic Parameters of Metamaterials with the Unit Cell of Symmetrically Arranged SRRs

2012 ◽  
Vol 531-532 ◽  
pp. 351-357
Author(s):  
Wang Zhou Zhang ◽  
Zhu Ying Li ◽  
Ye Liu
Keyword(s):  
Effective Permittivity ◽  
Split Ring Resonator ◽  
Index Of Refraction ◽  
Electromagnetic Parameters ◽  
Structured Materials ◽  
Left Handed ◽  
S Parameter ◽  
Circular Structure ◽  
Retrieval Result ◽  
Specific Frequency

Based on the principle that metamaterials-composite structured materials, in which permittivity(ε)and permeability(μ)are both negative in some frequencice, can be structured with periodically arranged SRRs and thin metallic wires which have negative effective permeability and negative effective permittivity respectively, the circular structure of SRRs was modified and a new split-ring resonator with symmetric structure was proposed. A detailed description of the design and simulation procedure was given simultaneously. According to the pattern of symmetric SRRs, ε and μ were calculated in analytic formula. Furthermore, metamaterials with symmetric SRRs was simulated with the software ANSOFT, and electromagnetic parameters were retried from S parameter. From analytic result and the retrieval result of electromagnetic parameters, left-handed behavior was obvious in a specific frequency range and the permittivity, the permeability and the index of refraction are all negative.

Discovery and Illustration of Novel Optimal Retrieval Result

2014 ◽  
Vol 36 (3) ◽  
pp. 643-653
Author(s):  
Yu HONG ◽  
Yang-Yang KANG ◽  
Jian-Min YAO ◽  
Qiao-Ming ZHU ◽  
Guo-Dong ZHOU
Keyword(s):  
Retrieval Result ◽  
Optimal Retrieval

Image Retrieval Method Based on Vision Feature of Color

2013 ◽  
Vol 303-306 ◽  
pp. 1406-1411
Author(s):  
Ying Meng Dai ◽  
Lin Feng Wei ◽  
Cong Luo
Keyword(s):  
Spatial Distribution ◽  
Image Retrieval ◽  
Good Accuracy ◽  
Color Histogram ◽  
Weighted Sums ◽  
Original Image ◽  
Retrieval Method ◽  
Color Histograms ◽  
Retrieval Result ◽  
Distinct Color

Color histogram is an important technique for color database retrieving, but it often ignores color’s spatial distribution information. This paper proposes an improved color histogram algorithm based on the HSV space, whose subspaces are non-equally quantized. The algorithm first proceeds annular partition on the original image, and then uses the method presented by Aibing Rao etc. [1] to count each partition. At last, it calculates the weighted sums for the distances between distinct color histograms. Experimental results demonstrate that the algorithm reduces the feature dimensions and keeps a good accuracy as well as the spatial distribution information. Thus, a better retrieval result is obtained.

scholarly journals Selecting the N-Top Retrieval Result Lists for an Effective Data Fusion

2010 ◽  
pp. 580-589 ◽  
Author(s):  
Antonio Juárez-González ◽  
Manuel Montes-y-Gómez ◽  
Luis Villaseñor-Pineda ◽  
David Pinto-Avendaño ◽  
Manuel Pérez-Coutiño
Keyword(s):  
Data Fusion ◽  
Retrieval Result

Improved Retrieval of Reflectivity Factor for Airborne Weather Radar

2014 ◽  
Vol 1073-1076 ◽  
pp. 611-614
Author(s):  
Tian Shun Xiang ◽  
Yong Li ◽  
Di Wu ◽  
Li He
Keyword(s):  
Estimation Method ◽  
Weather Radar ◽  
Radar Signal ◽  
Radar Signal Processing ◽  
Retrieval Result ◽  
Low Altitude ◽  
Weather Radar Signal Processing ◽  
Filling Coefficient ◽  
Radar Equation ◽  
Reflectivity Factor

For the airborne weather radar signal processing, the intensity of the meteorological targets is represented by the physical quantity called reflectivity factor. When observing the middle-or long-range meteorological targets at low altitude from a high-altitude radar platform, due to the incomplete beam filling, the retrieval result of the reflectivity factor is much less than the actual value. In this paper, we firstly introduce a beam filling coefficient into the weather radar equation and then present its estimation method based on the real-time radar operating parameters. The validity of the proposed method is then verified by processing the raw-data of the simulated meteorological targets.

Improving the similarity search between images of agricultural products: An approach based on fuzzy rough theory

2021 ◽  
pp. 1-10
Author(s):  
Poria Pirozmand ◽  
Ali Ebrahimnejad ◽  
Homayun Motameni ◽  
Kimia Rezaee Kalantari
Keyword(s):  
Similarity Search ◽  
Feature Vector ◽  
Agricultural Products ◽  
Huge Amount ◽  
Retrieval Accuracy ◽  
Retrieval Result ◽  
Rough Theory ◽  
Fuzzy Color Histogram

Many methods have been presented in recent years for identifying the quality of agricultural products using machine vision that due to the huge amount of redundant information and noisy data of images of products, the retrieval accuracy and speed of such methods were not much acceptable. All of them try to provide approaches to extract efficient features and determine optimal methods to measure similarity between images. One of the basic problems of these methods is determination of desirable features of the user as well as using an appropriate similarity measure. This study tries to recognize the importance of each feature according to user’s opinion in every feedback stage through using weighted feature vector, rough theory and fuzzy logic for identifying important features and finding a higher accuracy in retrieval result. The proposed method is compared with fuzzy color histogram, combined approach and fuzzy neighborhood entropy characterized by color location. The simulation results indicate that the proposed method has higher applicability in image marketing compared to the existing methods.

scholarly journals Content based video retrieval system using principal object analysis

2019 ◽  
Vol 14 (9) ◽  
pp. 24
Author(s):  
Bui Van Thinh ◽  
Tran Anh Tuan ◽  
Ngo Quoc Viet ◽  
Pham The Bao
Keyword(s):  
Retrieval System ◽  
Video Retrieval ◽  
Music History ◽  
Input Image ◽  
Speeded Up Robust Features ◽  
Video Clips ◽  
Tv Program ◽  
Retrieval Result ◽  
Program Show ◽  
Content Based Video Retrieval

Video retrieval is a searching problem on videos or clips based on the content of video clips which relates to the input image or video. Some recent approaches have been in challenging problem due to the diversity of video types, frame transitions and camera positions. Besides, that an appropriate measures is selected for the problem is a question. We propose a content based video retrieval system in some main steps resulting in a good performance. From a main video, we process extracting keyframes and principal objects using Segmentation of Aggregating Superpixels (SAS) algorithm. After that, Speeded Up Robust Features (SURF) are selected from those principal objects. Then, the model “Bag-of-words” in accompanied by SVM classification are applied to obtain the retrieval result. Our system is evaluated on over 300 videos in diversity from music, history, movie, sports, and natural scene to TV program show. 

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