Sonia Setia - Academia.edu (original) (raw)

Papers by Sonia Setia

LZW is one known popular dictionary based data compression adaptive algorithm. It is appropriate ... more LZW is one known popular dictionary based data compression adaptive algorithm. It is appropriate for communication, because it require no extra communication between sender and receiver. In this paper we present a scheme for dynamic dictionary size to overcome dictionary flushing out problem. We use multi levels for dictionary. In the first level we encode any string in dictionary using just 10 bits. In second level we encode any string in dictionary using just 11 bits. In general case for n 2 dictionary size we encode any string in dictionary using just (n+1) bits, n bits for data and 1 bit (M.S.B bit) used for parity bit.

Advances in Intelligent Systems and Computing, 2017

Exponential growth of web accesses on the Internet causes substantial delays in providing service... more Exponential growth of web accesses on the Internet causes substantial delays in providing services to the user. Web prefetching is an effective solution that can improve the performance of the web by reducing the latency perceived by the user. Content on the web page also provides meaningful data to predict the future requests. This paper presents a content-based semantic prefetching approach. The proposed approach basically works on the semantic preferences of the tokens present in the anchor text associated with the URLs. To make more accurate predictions, it also uses the semantic information which is explicitly embedded with each link. It then computes the semantic association between the tokens and links then associates weightage in order to improve the prediction accuracy. This prefetching scheme would be more effective for long browsing sessions and will achieve good hit rate.

International journal of innovative research and development, 2013

Data compression is a key component for data storage systems and for communication purposes. Lemp... more Data compression is a key component for data storage systems and for communication purposes. Lempel-Ziv-Welch (LZW) data compression algorithm is popular for data compression because it is an adaptive algorithm and achieves an excellent compromise between compression performance and speed of execution. LZW is a dictionary based data compression algorithm, which compress the data in a lossless manner so that no information is lost. But LZW algorithm fails in case of small amount of data. In this case it expands the data instead of compressing it. In this paper a system is proposed to achieve high compression even if data file contains small amount of data.

Association rule mining is the most popular technique in the area of data mining. The main task o... more Association rule mining is the most popular technique in the area of data mining. The main task of this technique is to find the frequent patterns by using minimum support thresholds decided by the user. The Apriori algorithm is a classical algorithm among association rule mining techniques. This algorithm is inefficient because it scans the database many times. Second, if the database is large, it takes too much time to scan the database. For many cases, it is difficult to discover association rules among the objects at low levels of abstraction. Association rules among various item sets of databases can be found at various levels of abstraction. Apriori algorithm does not mine the data on multiple levels of abstraction. Many algorithms in literature discussed this problem. This paper presents the survey on multi-level association rules and mining algorithms.

2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), 2016

A large growth of web uses on the Internet causes latency perceived by the user. Prefetching is a... more A large growth of web uses on the Internet causes latency perceived by the user. Prefetching is a good solution to this problem. Web page content provides the meaningful data to predict the coming requests in future. This paper presents a semantic prefetching technique which uses the content of the web page. The proposed technique works on the semantic preferences of the anchor text associated with the URL. This technique also uses the semantic information, explicitly embedded with each link, for more accurate predictions. It also computes the semantic association in order to improve the prediction accuracy. This prefetching technique would be more effective for long sessions and will achieve good hit rate.

International Journal of Engineering and Advanced Technology, 2019

An important issue incurred by users that limits the use of internet is the long web access delay... more An important issue incurred by users that limits the use of internet is the long web access delays. Most efficient way to solve this problem is to use “Prefetching”. This paper is an attempt to dynamically monitor the network bandwidth for which a neural network-based model has been worked upon. Prefetching is an effective and efficient technique for reducing users perceived latency. It is a technique that predicts & fetches the web pages in advance corresponding to the clients’ request, that will be accessed in future. Generally, this prediction is based on the historical information that the sever maintains for each web page it serves in a chronological order. This is a speculative technique where if predictions are incorrect then prefetching adds extra traffic to the network, which is seriously negating the network performance. Therefore, there is critical need of a mechanism that could analyze the network bandwidth of the system before prefetching is done. Based on network condi...

Ijrcct, Dec 30, 2013

Web caching and web prefetching are the two major areas of research focused at reducing the user ... more Web caching and web prefetching are the two major areas of research focused at reducing the user perceived latency. Both if used well can greatly help in reducing this latency as web caching helps in exploiting temporal latency while web prefetching helps in exploiting spatial latency. However if prefetched pages are not visited by the users in their future accesses, they can increase the network traffic and overload the web server. This paper aims at surveying various research papers who have worked in this direction.

Clustering is one of the important techniques in Data Mining to group the related data. Clusterin... more Clustering is one of the important techniques in Data Mining to group the related data. Clustering can be applied on numerical data as well as web objects such as URLs, websites, documents, keywords etc. which is the building block for many recommender systems as well as prediction models. The objective of this research article is to develop an optimal clustering approach which considers semantics of web objects to cluster them in a group. More so importantly, the purpose of the proposed work is to strictly improve the computation time of clustering process. In order to achieve the desired objectives, following two contributions have been proposed to improve the clustering approach 1) Semantic Similarity Measure based on Wu-Palmer Semantics based similarity 2). Two-Level Densitybased Clustering technique to reduce the computational complexity of density based clustering approach. The efficacy of the proposed method has been analyzed on AOL search logs containing 20 million web queri...

Web prefetching is one of the significant techniques used to alleviate the rendering latency perc... more Web prefetching is one of the significant techniques used to alleviate the rendering latency perceived by users. Various researchers have supported the concept of Web prefetching in many forms by providing numerous methods that have increased the speed of web page delivery, but delays still are incurred because they lack in the relevancy of the results. Prefetching technique could be improved by analyzing the semantics of content enhanced with domain ontology. In view of this, a Semantic Prefetching System has been proposed that makes use of both the usage data and the semantics of the content information to predict the user‘s behavior. Web content is semantically annotated with ontology terms. Semantic Weighted Log Records are introduced which contains the knowledge derived from the ontology and thesaurus, thereby allowing semantically focused set of prediction to be achieved.

Scientific Programming

The continuous growth of the World Wide Web has led to the problem of long access delays. To redu... more The continuous growth of the World Wide Web has led to the problem of long access delays. To reduce this delay, prefetching techniques have been used to predict the users’ browsing behavior to fetch the web pages before the user explicitly demands that web page. To make near accurate predictions for users’ search behavior is a complex task faced by researchers for many years. For this, various web mining techniques have been used. However, it is observed that either of the methods has its own set of drawbacks. In this paper, a novel approach has been proposed to make a hybrid prediction model that integrates usage mining and content mining techniques to tackle the individual challenges of both these approaches. The proposed method uses N-gram parsing along with the click count of the queries to capture more contextual information as an effort to improve the prediction of web pages. Evaluation of the proposed hybrid approach has been done by using AOL search logs, which shows a 26% i...

LZW is one known popular dictionary based data compression adaptive algorithm. It is appropriate ... more LZW is one known popular dictionary based data compression adaptive algorithm. It is appropriate for communication, because it require no extra communication between sender and receiver. In this paper we present a scheme for dynamic dictionary size to overcome dictionary flushing out problem. We use multi levels for dictionary. In the first level we encode any string in dictionary using just 10 bits. In second level we encode any string in dictionary using just 11 bits. In general case for n 2 dictionary size we encode any string in dictionary using just (n+1) bits, n bits for data and 1 bit (M.S.B bit) used for parity bit.

Advances in Intelligent Systems and Computing, 2017

Exponential growth of web accesses on the Internet causes substantial delays in providing service... more Exponential growth of web accesses on the Internet causes substantial delays in providing services to the user. Web prefetching is an effective solution that can improve the performance of the web by reducing the latency perceived by the user. Content on the web page also provides meaningful data to predict the future requests. This paper presents a content-based semantic prefetching approach. The proposed approach basically works on the semantic preferences of the tokens present in the anchor text associated with the URLs. To make more accurate predictions, it also uses the semantic information which is explicitly embedded with each link. It then computes the semantic association between the tokens and links then associates weightage in order to improve the prediction accuracy. This prefetching scheme would be more effective for long browsing sessions and will achieve good hit rate.

International journal of innovative research and development, 2013

Data compression is a key component for data storage systems and for communication purposes. Lemp... more Data compression is a key component for data storage systems and for communication purposes. Lempel-Ziv-Welch (LZW) data compression algorithm is popular for data compression because it is an adaptive algorithm and achieves an excellent compromise between compression performance and speed of execution. LZW is a dictionary based data compression algorithm, which compress the data in a lossless manner so that no information is lost. But LZW algorithm fails in case of small amount of data. In this case it expands the data instead of compressing it. In this paper a system is proposed to achieve high compression even if data file contains small amount of data.

Association rule mining is the most popular technique in the area of data mining. The main task o... more Association rule mining is the most popular technique in the area of data mining. The main task of this technique is to find the frequent patterns by using minimum support thresholds decided by the user. The Apriori algorithm is a classical algorithm among association rule mining techniques. This algorithm is inefficient because it scans the database many times. Second, if the database is large, it takes too much time to scan the database. For many cases, it is difficult to discover association rules among the objects at low levels of abstraction. Association rules among various item sets of databases can be found at various levels of abstraction. Apriori algorithm does not mine the data on multiple levels of abstraction. Many algorithms in literature discussed this problem. This paper presents the survey on multi-level association rules and mining algorithms.

2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), 2016

A large growth of web uses on the Internet causes latency perceived by the user. Prefetching is a... more A large growth of web uses on the Internet causes latency perceived by the user. Prefetching is a good solution to this problem. Web page content provides the meaningful data to predict the coming requests in future. This paper presents a semantic prefetching technique which uses the content of the web page. The proposed technique works on the semantic preferences of the anchor text associated with the URL. This technique also uses the semantic information, explicitly embedded with each link, for more accurate predictions. It also computes the semantic association in order to improve the prediction accuracy. This prefetching technique would be more effective for long sessions and will achieve good hit rate.

International Journal of Engineering and Advanced Technology, 2019

An important issue incurred by users that limits the use of internet is the long web access delay... more An important issue incurred by users that limits the use of internet is the long web access delays. Most efficient way to solve this problem is to use “Prefetching”. This paper is an attempt to dynamically monitor the network bandwidth for which a neural network-based model has been worked upon. Prefetching is an effective and efficient technique for reducing users perceived latency. It is a technique that predicts & fetches the web pages in advance corresponding to the clients’ request, that will be accessed in future. Generally, this prediction is based on the historical information that the sever maintains for each web page it serves in a chronological order. This is a speculative technique where if predictions are incorrect then prefetching adds extra traffic to the network, which is seriously negating the network performance. Therefore, there is critical need of a mechanism that could analyze the network bandwidth of the system before prefetching is done. Based on network condi...

Ijrcct, Dec 30, 2013

Web caching and web prefetching are the two major areas of research focused at reducing the user ... more Web caching and web prefetching are the two major areas of research focused at reducing the user perceived latency. Both if used well can greatly help in reducing this latency as web caching helps in exploiting temporal latency while web prefetching helps in exploiting spatial latency. However if prefetched pages are not visited by the users in their future accesses, they can increase the network traffic and overload the web server. This paper aims at surveying various research papers who have worked in this direction.

Clustering is one of the important techniques in Data Mining to group the related data. Clusterin... more Clustering is one of the important techniques in Data Mining to group the related data. Clustering can be applied on numerical data as well as web objects such as URLs, websites, documents, keywords etc. which is the building block for many recommender systems as well as prediction models. The objective of this research article is to develop an optimal clustering approach which considers semantics of web objects to cluster them in a group. More so importantly, the purpose of the proposed work is to strictly improve the computation time of clustering process. In order to achieve the desired objectives, following two contributions have been proposed to improve the clustering approach 1) Semantic Similarity Measure based on Wu-Palmer Semantics based similarity 2). Two-Level Densitybased Clustering technique to reduce the computational complexity of density based clustering approach. The efficacy of the proposed method has been analyzed on AOL search logs containing 20 million web queri...

Web prefetching is one of the significant techniques used to alleviate the rendering latency perc... more Web prefetching is one of the significant techniques used to alleviate the rendering latency perceived by users. Various researchers have supported the concept of Web prefetching in many forms by providing numerous methods that have increased the speed of web page delivery, but delays still are incurred because they lack in the relevancy of the results. Prefetching technique could be improved by analyzing the semantics of content enhanced with domain ontology. In view of this, a Semantic Prefetching System has been proposed that makes use of both the usage data and the semantics of the content information to predict the user‘s behavior. Web content is semantically annotated with ontology terms. Semantic Weighted Log Records are introduced which contains the knowledge derived from the ontology and thesaurus, thereby allowing semantically focused set of prediction to be achieved.

Scientific Programming

The continuous growth of the World Wide Web has led to the problem of long access delays. To redu... more The continuous growth of the World Wide Web has led to the problem of long access delays. To reduce this delay, prefetching techniques have been used to predict the users’ browsing behavior to fetch the web pages before the user explicitly demands that web page. To make near accurate predictions for users’ search behavior is a complex task faced by researchers for many years. For this, various web mining techniques have been used. However, it is observed that either of the methods has its own set of drawbacks. In this paper, a novel approach has been proposed to make a hybrid prediction model that integrates usage mining and content mining techniques to tackle the individual challenges of both these approaches. The proposed method uses N-gram parsing along with the click count of the queries to capture more contextual information as an effort to improve the prediction of web pages. Evaluation of the proposed hybrid approach has been done by using AOL search logs, which shows a 26% i...