Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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CSTSDE991B1
Rajesh Kulkarni
The objective of the proposal is to analyze the user search goals for a query which can be very useful in improving search engine relevance and user experience. Although the research on inferring user goals or intents for text search has received much attention, little has been proposed for image search with visual information. In this project, we propose a novel approach to capture user search goals in image search by exploring images which are extracted by mining single sessions in user click-through logs to reflect user information needs. Moreover, we also propose a novel evaluation criterion to determine the number of user search goals for a query. Modified re-ranking and semantic similarity algorithm are part of this proposal. Experimental results demonstrate the effectiveness of the proposed method.
Shamali Kishor Kherdikar. 2014. \u201cEnhanced Re-ranking and Semantic Similarity Algorithm for Image Search Goals using Click-through Logs\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 14 (GJCST Volume 14 Issue C6): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
The methods for personal identification and authentication are no exception.
Total Score: 102
Country: India
Subject: Global Journal of Computer Science and Technology - C: Software & Data Engineering
Authors: Shamali Kishor Kherdikar, Rajesh Kulkarni (PhD/Dr. count: 0)
View Count (all-time): 239
Total Views (Real + Logic): 8660
Total Downloads (simulated): 2360
Publish Date: 2014 09, Sat
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Neural Networks and Rules-based Systems used to Find Rational and
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The objective of the proposal is to analyze the user search goals for a query which can be very useful in improving search engine relevance and user experience. Although the research on inferring user goals or intents for text search has received much attention, little has been proposed for image search with visual information. In this project, we propose a novel approach to capture user search goals in image search by exploring images which are extracted by mining single sessions in user click-through logs to reflect user information needs. Moreover, we also propose a novel evaluation criterion to determine the number of user search goals for a query. Modified re-ranking and semantic similarity algorithm are part of this proposal. Experimental results demonstrate the effectiveness of the proposed method.
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