Top PDF Semantic Query Expansion for Arabic Information Retrieval

Semantic Query Expansion for Arabic Information Retrieval

Semantic Query Expansion for Arabic Information Retrieval

Traditional keyword based search is found to have some limitations. Such as word sense ambiguity, and the query intent ambiguity which can hurt the precision. Semantic search uses the contextual meaning of terms in addition to the semantic matching techniques in order to overcome these limitations. This paper introduces a query expansion approach using an ontology built from Wikipedia pages in addition to other thesaurus to improve search accuracy for Arabic language. Our approach outperformed the traditional keyword based approach in terms of both F-score and NDCG measures.
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND 
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND DOCUMENT RANKING

Sentence similarity is needed during clustering to establish closeness between question objects. Sentence similarity between two questions can be established using either statistic similarity or semantic similarity or both. It is a common practice in traditional document similarity measures to represent document with high dimensional space in which each word in the document is considered as a dimension, which is the TFIDF. This practice does yield good result in large document retrieval applications due to the fact that the documents share a lot of words. Similarity calculation between questions cannot toll this line since question sentence contain just few words. Using high dimension representation with questions will make the vector space to be very sparse and will lead to a poor performance. An approach used by [23] is recommended. Similarity between two questions is performed using a low dimension vector space composed of the words of the two questions instead of vector space of all question words.
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND 
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND DOCUMENT RANKING

To avoid complexity, the existing FFA structures are employed for some sub-filter blocks that contain no symmetric coefficients which have more compact operations in preprocessing and po[r]

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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND 
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND DOCUMENT RANKING

An interconnected two-area system thermal power system having one reheat turbine and one non-reheat turbine with SMES unit in each area in the deregulated environment shown in Figure.1 i[r]

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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND 
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND DOCUMENT RANKING

In conventional scheduling, a middle control decision maker is always there ready with all the appropriate information about the issues, therefore requested to obtain a solution that completes all the required side constraints, optimizing an overall performance condition. The setup of the on- demand GaaS Cloud environment is such that conditional decisions are taken by a number of autonomous components and the components may be aiming at optimizing their own objectives rather than the performance of the structure in total [2]. Entities in the on-demand GaaS Cloud setup are self-interested and always ready to distribute their resources. The on-demand GaaS Cloud environment calls for models and algorithms that take the premeditated activities of individual entities into account, and concurrently keep track of all the overall performance of the structure.
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND 
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND DOCUMENT RANKING

8 to create benchmark corpus. This system is very effective because it retrieves both exact matches and relevant matches based on the user query with the help of query expansion technique. It fetches and provides information to user from most likely information to least likely information with the help of document ranking method. Multiple terms in query also retrieves information easily and effectively with the help of enhanced inverted index. Stemming Technique reduces the size of the inverted index. The searching time will be reduced because unique or root words can be obtained by Paice / Husk stemming algorithm. The indexing time of proposed inverted indexing increases when the system founds more unique terms in the document as in figure 7. Otherwise it simply increments the frequency count of the term.
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A Study on the Semantic Relatedness of Query and Document Terms in Information Retrieval

A Study on the Semantic Relatedness of Query and Document Terms in Information Retrieval

We first proved that there exists a vocabulary gap in the test collection between queries and doc- uments and that it can be reduced by employing a concept vector based measure for SR with any of the three knowledge bases. Using WordNet to au- tomatically annotate the lexical semantic relations of query and document terms, we found that cohy- ponymy and synonymy are the most frequent clas- sical relation types. Although the percentage of annotated relations for which also the SR measure computed values above a predefined threshold was at best 21%, the average number of SR scores for classical and non-classical relations were almost consistently higher for relevant documents.
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A Generalized Vector Space Model for Text Retrieval Based on Semantic Relatedness

A Generalized Vector Space Model for Text Retrieval Based on Semantic Relatedness

In this work, we argue that the incorporation of semantic information into a GVSM retrieval model can improve performance by considering the semantic relatedness between the query and document terms. The proposed model extends the traditional VSM with term to term relatedness measured with the use of WordNet. The success of the method lies in three important factors, which also constitute the points of our contribution: 1) a new measure for computing semantic relatedness between terms which takes into account relation weights, and senses’ depth; 2) a new GVSM re- trieval model, which incorporates the aforemen- tioned semantic relatedness measure; 3) exploita- tion of all the semantic information a thesaurus can offer, including semantic relations crossing parts of speech (POS). Experimental evaluation in three TREC collections shows that the pro- posed model can improve in certain cases the performance of the standard TF-IDF VSM. The rest of the paper is organized as follows: Section 2 presents preliminary concepts, regarding VSM and GVSM. Section 3 presents the term seman- tic relatedness measure and the proposed GVSM. Section 4 analyzes the experimental results, and Section 5 concludes and gives pointers to future work.
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND 
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND DOCUMENT RANKING

minimize the time spent in idle mode, taking into account not only the consumed power, but also the end-to-end transmission delay. This is accomplished through the synchronization of the wake up times of all the nodes in the sensor network. More specifically, the gateway gathers the available connectivity information between all the nodes in the network, and uses existing energy- efficient routing algorithms to calculate the paths from each node to the gateway. Then, the gateway constructs a TDMA frame which ensures the collision avoidance. This schedule is broadcasted back to the sensor nodes, allowing every sensor to know when it can transmit and when it should expect to receive a packet.
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND 
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND DOCUMENT RANKING

The key to reverse engineering in visual perception is the understanding of visual information represented and processed in the brain. While it is clear that geometry and visual perception are closely related, very little is known about this relation beyond its early retinotopic association. In visual perception studies, retinotopic refers to the visual process where object in the environment are projected to photo-receptors in the retina in a similar manner as appearance models in a digital image. Nevertheless, a recent study on human vision [3] shows that the representation in higher visual areas of the visual cortex occurs in a nonretinotopic manner: visual perception seems to create dynamic layers for each moving object in the scene. This representation suggests that the appearance of the objects and their positions are marginal independent.
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND 
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND DOCUMENT RANKING

Mohammdy using the same assumption of NSPI algorithm in recoverig SLC-off image on study area in Iran. Furthermore, LLHM approach was applied to predict the remaining un-scanned values. Unsupervised classification was applied on both recovered SLC-off and basic TM images for quantitative evaluation and the results show that the percent area of classes was comparable[26]. Zeng proposed an integrated approach to recover the missing pixels by using a multi temporal algorithm followed by the non - reference approach. Weighted Linear Regression (WLR) algorithm was used to reconstruct the un-scanned locations in a complicated landscape area using an auxiliary information from multi temporal SLC-off images, then the regularization algorithm was used to recover the remaining gaps when the auxiliary multi-temporal information cannot reconstruct all the un-scanned pixels. Simulated and real ETM+ images were used to experiment the proposed method, then compare the results with results of two conventional methods (LLHM and NSPI) which applied to the same tested images. Four statistical indices were used to assess the results quantitatively.
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND 
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND DOCUMENT RANKING

SEVERITY SCORING OF SYMPTOMS ASSOCIATED WITH CARPAL TUNNEL SYNDROME BASED ON RECALL OF COMPUTER GAME PLAYING EXPERIENCES 1.. NURUL HIDAYAH MAT ZAIN, 2AZIZAH JAAFAR, 3FARIZA HANIS ABDUL R[r]

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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND 
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND DOCUMENT RANKING

From the Table 1, it is obtained information that there were 3 patients AAA with homogeneous thrombus, 8 patients with heterogeneous thrombus and 1 patient with indefinite thrombus categories. The maximum diameter, thrombus area and thrombus categories have been obtained from the previous article [17]. Values of blood flow velocity have been calculated based on the maximum speed data obtained from the combined 3D instantaneous velocity in each direction vector (x, y, and z). And the volume of blood flow obtained simultaneously with 4D reconstruction image is the ultimate goal of this research.
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND 
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND DOCUMENT RANKING

Fei et al presented a key-exposure free online/offline signcryption scheme .Their scheme proved indistinguishable against adaptive chosen-cipher text attacks (IND-CCA2) and unforgeable against chosen-message attacks (EUF-CMA). And their scheme requires none of the recipient's public information in the offline phase and hence makes practical sense [10]. The Secure Hash Algorithm is one of the number of cryptographic hash functions.SHA- 0:Aheteronym applied to the original version of the 160-bit hash function published in 1993 under the name "SHA". It was withdrawn shortly after publication due to an undisclosed "significant flaw" and replaced by the slightly revised version SHA-1.
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND 
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND DOCUMENT RANKING

Pattern deploying is used to discover the pattern in effective manner. That can easily eliminate the overlapping among the pattern; assign the frequency to term weighting method, which is reduce the both searching space and time complexity. It improves the performance of closed pattern as well as normalizing the pattern. After normalization which accurately evaluate the pattern weights, and also extracting the more semantic information from textual documents.

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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND 
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND DOCUMENT RANKING

analysis {Load Flow and Short Circuit} are preformed to verify the steady state behavior during grid planning and generation transmission expansion. Transient stability is not considered in the planning stage to study the dynamic behavior of the power system due to non availability of simulation model, insufficient input data, non availability of robust software etc., Major block outs on July 30 and 31 st 2012 in northern grid of india change the conventional mindsets and emphasis transient stability as a part of grid planning [30].
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND 
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND DOCUMENT RANKING

Classifications of the connections among entity types: In the design of the proposed model of Software security awareness’s • Entity type 1 measure size of the external security awarenes[r]

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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND 
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND DOCUMENT RANKING

At the stage implementation of augmented reality systems, will be divided into two phases, namely the development of marker through student textbooks and application simulation content p[r]

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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND 
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 AN EFFICIENT INFORMATION RETRIEVAL SYSTEM USING QUERY EXPANSION AND DOCUMENT RANKING

Studies of feature extraction using Wavelets and SVM as classifier have been done since several decades ago with objects such as images. Research for palm print with very successful result had been done with better accuracy when using the combination of dual tree complex wavelets with SVM using Gaussian function kernel [4]. Classification of music using multilinear approaches combined with SVM obtained accuracy of 78.2%, 77.9%, 75.01%, 80.47%, 80.95%, and 78.53%18. Other experiments regarding music genre classification using temporal information and SVM obtained result of 78.6% in classifying 10 music genres [26].
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Mathematical Information Retrieval based on Type Embeddings and Query Expansion

Mathematical Information Retrieval based on Type Embeddings and Query Expansion

values for these query expansion models are also taken from Cummins et al. (2015). LMs with QE are used to determine how type-based QE performs in comparison to state-of-the-art term-based QE. Automatic QE using top TF-IDF terms (TFIDF-Exp). In this model, the query is expanded using the top s terms in the query as determined by document collection-wide TF-IDF scores. Stopwords and words with term frequency lower than 50 are excluded. Like before, each selected term is expanded using its n-nearest neighbours in a word embedding space (skip-gram, window size =10). The model has two parameters: pool size (n) and seed size (s). We found experimentally that the model performs best for n = 1 and s = 1. This baseline is used to determine whether any performance improvements obtained by type-based QE using an embedding space are due to types, rather than the use of embedding spaces in general.
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