Intelligent Subject and Knowledge Retrieval Algorithm Based on Ontology

2014 ◽  
Vol 687-691 ◽  
pp. 1452-1456
Author(s):  
Ting Ting Liang
Keyword(s):  
Retrieval System ◽  
Concept Map ◽  
Retrieval Algorithm ◽  
Knowledge Retrieval ◽  
Retrieval Process ◽  
Matching Method ◽  
Interactive Genetic Algorithm ◽  
Application Model ◽  
Matching Efficiency ◽  
High Intelligence

For the problems of obscure demand of users, insufficiency and difficulty in correct acquisition in the process of knowledge retrieval, this paper combines with basic theory of interactive genetic algorithm to discuss its application model in the process of requirement and acquisition of knowledge retrieval. And then, it uses the interactive information produced in the retrieval process to make improvement on matching method based on concept map. It uses the interactive information produced in the retrieval process to calculate weight of users to search concept, which enhances the knowledge matching efficiency of concept map. Through test, it compares that intelligent knowledge retrieval system based on ontology has double advantages with high intelligence and efficiency.

FROM ADAPTATION-GUIDED RETRIEVAL TO REUSE-GUIDED RETRIEVAL: APPLICATION TO CASE RETRIEVAL NET MEMORY MODEL

2013 ◽  
Vol 12 (04) ◽  
pp. 757-787 ◽  
Author(s):  
NABILA NOUAOURIA ◽  
MOUNIR BOUKADOUM
Keyword(s):  
General Framework ◽  
Retrieval System ◽  
Similar Case ◽  
Memory Model ◽  
Case Based Reasoning ◽  
Retrieval Process ◽  
Case Retrieval ◽  
Full Cost ◽  
Adaptation Cost ◽  
Process Adaptation

In Case-Based Reasoning (CBR), case retrieval is generally guided by similarity. However, the most similar case may not be the easiest one to reuse (hard to adapt). As recommended by Smyth and Keane, it might be more efficient to use an adaptability criterion to guide the retrieval process (adaptation-guided retrieval or AGR). In the same trend but with the goal of optimizing case reuse, our approach is to consider what is similar to copy and what is different to adapt during the retrieval stage. We introduce a more general framework for retrieval, namely the reuse-guided retrieval (RGR). The goal of this paper is twofold: first, it proposes a case retrieval approach that relies on reuse cost; then, it illustrates its use by integrating adaptation cost into the case retrieval net (CRN) memory model, a similarity-based case retrieval system. The described retrieval framework optimizes case reuse early in the inference cycle, without incurring the full cost of an adaptation step. Our results on two case studies reveal that the proposed approach yields better recall quality than CRN's similarity only-based retrieval while having similar computational complexity.

scholarly journals Image Retrieval Using Data Mining Technique

2020 ◽  
pp. 2115-2125
Author(s):  
Sarmad T. Abdul-Samad ◽  
Sawsan Kamal
Keyword(s):  
Image Retrieval ◽  
User Satisfaction ◽  
Clustering Algorithm ◽  
Retrieval System ◽  
Spatial Information ◽  
Search Space ◽  
Extraction Process ◽  
Retrieval Process ◽  
Data Mining Technique ◽  
Image Retrieval System

Even though image retrieval is considered as one of the most important research areas in the last two decades, there is still room for improvement since it is still not satisfying for many users. Two of the major problems which need to be improved are the accuracy and the speed of the image retrieval system, in order to achieve user satisfaction and also to make the image retrieval system suitable for all platforms. In this work, the proposed retrieval system uses features with spatial information to analyze the visual content of the image. Then, the feature extraction process is followed by applying the fuzzy c-means (FCM) clustering algorithm to reduce the search space and speed up the retrieval process. The experimental results show that using the spatial features increases the system accuracy and that the clustering algorithm speeds up the image retrieval process. This shows that the proposed system works with texture and non-texture images.  

scholarly journals INDONESIAN-TRANSLATED HADITH CONTENT WEIGHTING IN PSEUDO-RELEVANCE FEEDBACK QUERY EXPANSION

Kursor ◽  
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ivanda Zevi Amalia ◽  
Akbar Noto Ponco Bimantoro ◽  
Agus Zainal Arifin ◽  
Maryamah Faisol ◽  
Rarasmaya Indraswari ◽  
...  
Keyword(s):  
Query Expansion ◽  
Retrieval System ◽  
Named Entity Recognition ◽  
Entity Recognition ◽  
Retrieval Process ◽  
Retrieval Performance ◽  
Additional Information ◽  
Named Entity ◽  
Story Content ◽  
Test Scenarios

In general, hadith consists of isnad and matan (content). Matan can be separated into several components for example a story, main content, and some additional information. Other texts besides main content, such as isnad and story can interfere the retrieval process of relevant documents because most users typically use simple queries. Thus, in this paper, we proposed a Named Entity Recognition (NER) component weighting model in improving the Indonesian hadith retrieval system. We did 3 test scenarios, the first scenario (S1) did not separate the hadith into several components, the second scenario (S2) separated the hadith into 2 components, isnad and matan, and the third scenario separated the hadith into 4 components, isnad, background story, content, and additional information. From the experimental results, it is found that the TF-IDF with rocchio algorithm in query expansion outperforms DocVec. Also, separation and weighting of the hadith components affect the retrieval performance because isnad can be considered as noise in a query. Separation of 2 separate components had the best overall results in general although 4 separate components showed better results in some cases with precision up to 100% and 70% recall.

Evaluation of Light Inspired Optimization Algorithm-Based Image Retrieval

2014 ◽  
Vol 573 ◽  
pp. 529-536
Author(s):  
T. Kanimozhi ◽  
K. Latha
Keyword(s):  
Image Retrieval ◽  
Firefly Algorithm ◽  
Retrieval System ◽  
Computation Time ◽  
Image Databases ◽  
Image Search ◽  
Retrieval Process ◽  
Large Collection ◽  
Image Retrieval System ◽  
Unique Method

Image retrieval system becoming a more popular in all the disciplines of image search. In real-time, interactive image retrieval system has become more accurate, fast and scalable to large collection of image databases. This paper presents a unique method for an image retrieval system based on firefly algorithm, which improve the accuracy and computation time of the image retrieval system. The firefly algorithm is utilized to optimize the image retrieval process via search for nearly optimal combinations between the corresponding features as well as finding out approximate optimized weights for similarities with respect to the features. The proposed method is able to dynamically reflect the user’s intention in the retrieval process by optimizing the objective function. The Efficiency of the proposed method is compared with other existing image retrieval methods through precision and recall. The performance of the method is experimented on the Corel and Caltech database images.

GPKRS: A GPU-Enhanced Product Knowledge Retrieval System

2021 ◽  
pp. 446-451
Author(s):  
Yuming Lin ◽  
Hao Song ◽  
Chuangxin Fang ◽  
You Li
Keyword(s):  
Retrieval System ◽  
Product Knowledge ◽  
Knowledge Retrieval

Semantic / Fuzzy Information Retrieval System

2017 ◽  
Vol 12 (1) ◽  
pp. 37-56
Author(s):  
Mounira Chkiwa ◽  
Anis Jedidi ◽  
Faiez Gargouri
Keyword(s):  
Fuzzy Logic ◽  
Information Retrieval ◽  
Semantic Web ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Retrieval Process ◽  
Fuzzy Information ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Fuzzy Information Retrieval

In this paper, the authors present an overall description of their information retrieval system which makes a practical collaboration between Semantic Web and Fuzzy logic in order to have profit from their advantages in the information retrieval domain. Their system is dedicated for kids, for this reason the semantic/fuzzy collaboration materialized must be in the background of the information retrieval process because such category of users cannot certainly control semantic web technologies neither fuzzy logic commands. In this paper, the authors present the different services proposed by their system and how they use Semantic Web and Fuzzy logic to develop it. Evaluation tests of the system using universal measures show clearly its efficiency.

Data Mining Based Intelligent Retrieval Algorithm and its Application

2015 ◽  
Vol 742 ◽  
pp. 340-343
Author(s):  
Chun Ping Wang
Keyword(s):  
Information Retrieval ◽  
Digital Libraries ◽  
Retrieval System ◽  
Data Retrieval ◽  
Retrieval Algorithm ◽  
Accurate Information ◽  
Intelligent Information Retrieval ◽  
Intelligent Information ◽  
Mining Algorithms ◽  
Potential Use

Mathematical model of information retrieval algorithm retrieves digital libraries involved, it is very important to design an algorithm to make the best of the books, in order to extract the required information, including the association rules and classification method for from the database predicting the reader and potential use of fast and accurate information. In this paper, the intelligent data retrieval books mining algorithms to analyze, you can study the books of intelligent retrieval application, until the actual retrieval algorithm to solve the model first developed to meet the requirements, design a library of books intelligent information retrieval system .

CONTENT BASED IMAGE RETRIEVAL USING DISCRETE WAVELET TRANSFORM

2004 ◽  
Vol 18 (01) ◽  
pp. 19-32 ◽  
Author(s):  
SAEID BELKASIM ◽  
XIANYU HONG ◽  
O. BASIR
Keyword(s):  
Wavelet Transform ◽  
Image Retrieval ◽  
Discrete Wavelet Transform ◽  
Retrieval System ◽  
Industrial Applications ◽  
Discrete Wavelet ◽  
Retrieval Process ◽  
System A ◽  
Image Transforms ◽  
The Common

Image retrieval plays an important role in a broad spectrum of applications. Contentbased retrieval (CBR) is one of the popular choices in many biomedical and industrial applications. Discrete image transforms have been widely studied and suggested for many image retrieval applications. The Discrete Wavelet Transform (DWT) is one of the most popular transforms recently applied to many image processing applications. The Daubechies wavelet can be used to form the basis for extracting features in retrieving images based on the description of a particular object within the scene. This wavelet is widely used for image compression. In this paper we highlight the common features between compression and retrieval. Several examples are used to test the DWT retrieval system. A comparison between DWT and Discrete Cosine Transform (DCT) is also made. The retrieval system using DWT requires preprocessing and normalization of images, which might slow down the retrieval process. The accuracy of the retrieval using DWT has been significantly improved by incorporating efficient K-Neighbor Nearest Distance (KNND) measure in our system.

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