2. Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/1/7
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Item Quality driven web service selection and ranking(2008) D'Mello, D.A.; Ananthanarayana, V.S.The increasing number of Web service providers with numerous functionally similar or same Web services produced a new problem of choosing a suitable Web service for the requester based on his expectations. The Quality of Service (QoS) can be used to select and rank functionally similar Web services. In this paper we define four Web service provider qualities to distinguish functionally similar and qualitatively competitive Web services. The main objective of this paper is to explore the mechanism which breaks the tie that may arise among functionally similar and qualitatively equivalent (competitive) Web services during Web service selection and ranking. � 2008 IEEE.Item Prefix-Suffix trees: A novel scheme for compact representation of large datasets(2007) Pai, R.M.; Ananthanarayana, V.S.An important goal in data mining is to generate an abstraction of the data. Such an abstraction helps in reducing the time and space requirements of the overall decision making process. It is also important that the abstraction be generated from the data in small number of scans. In this paper we propose a novel scheme called Prefix-Suffix trees for compact storage of patterns in data mining, which forms an abstraction of the patterns, and which is generated from the data in a single scan. This abstraction takes less amount of space and hence forms a compact storage of patterns. Further, we propose a clustering algorithm based on this storage and prove experimentally that this type of storage reduces the space and time. This has been established by considering large data sets of handwritten numerals namely the OCR data, the MNIST data and the USPS data. The proposed algorithm is compared with other similar algorithms and the efficacy of our scheme is thus established. � Springer-Verlag Berlin Heidelberg 2007.Item Parallel method for discovering frequent itemsets using weighted tree approach(2009) Kumar, P.; Ananthanarayana, V.S.Every element of the transaction in a transaction database may contain the components such as item number, quantity, cost of the item bought and some other relevant information of the customer. Most of the association rules mining algorithms to discover frequent itemsets do not consider the components such as quantity, cost etc. In a large database it is possible that even if the itemset appears in a very few transactions, it may be purchased in a large quantity. Further, this may lead to very high profit. Therefore these components are the most important information and without which it may cause the lose of information. This motivated us to propose a parallel algorithm to discover all frequent itemsets based on the quantity of the item bought in a single scan of the database. This method achieves its efficiency by applying two new ideas. Firstly, transaction database is converted into an abstraction called Weighted Tree that prevents multiple scanning of the database during the mining phase. This data structure is replicated among the parallel nodes. Secondly, for each frequent item assigned to a parallel node, an item tree is constructed and frequent itemsets are mined from this tree based on weighted minimum support. � 2009 IEEE.Item EfficientTreeMiner: Mining frequent induced substructures from XML documents without candidate generation(2006) Santhi Thilagam, P.; Ananthanarayana, V.S.Tree structures are used extensively in domains such as XML databases, computational biology, pattern recognition, computer networks, web mining, multi-relational data mining and so on. In this paper, we present an EfficientTreeMiner, a computationally efficient algorithm that discovers all frequently occurring induced subtrees in a database of labeled rooted unordered trees. The proposed algorithm mines frequent subtrees without generating any candidate subtrees. Efficiency is achieved by compressing the large database into a condensed data structure, namely prefix string representation, which reduces space complexity and by adopting a Frequent Immediate Descendents method that avoids the costly generation of candidate sets. Experimental results show that our algorithm has less time complexity when compared to existing approaches and is also scalable for mining both long and short frequent subtrees. � 2006 IEEE.Item Efficient mining of frequent rooted continuous directed subgraphs(2006) Sreenivasa, G.J.; Ananthanarayana, V.S.Mining frequent rooted continuous directed (RCD) subgraphs is very useful in Web usage mining domain. We formulate the problem of mining RCD subgraphs in a database of rooted labeled continuous directed graphs. We propose a novel approach of merging like RCD subgraphs. This approach builds a Pattern Super Graph (PSG) structure. This PSG is a compact structure and ideal for extracting frequent patterns in the form of RCD subgraphs. The PSG based mine avoids costly, repeated database scans and there is no generation of candidates. Results obtained are appreciating the approach proposed. � 2006 IEEE.Item Effective web service discovery based on functional semantics(2009) D'Mello, D.A.; Ananthanarayana, V.S.Web service discovery is a mechanism which facilitates an access to the Web service descriptions. UDDI facilitates the discovery based on the service functionality through keyword and category matching. Such discovery techniques do not consider the semantics and user context as they are too syntactic in nature. In this paper, we propose a well formed functional semantics to describe an operation of a Web service. We design the extendible functional knowledge to map the requested or published operation descriptions into an abstract operation. The experimentation shows that, the proposed functional semantics based discovery mechanism has better performance in terms of precision and recall. � 2009 IEEE.Item Business offer driven dynamic web service selection(2008) D?Mello, D.A.; Ananthanarayana, V.S.; Achar, R.In today's business environment, the business offers have an inevitable importance in giving the buyer the most profitable deal. In order to improve the business, the service providers attract the customers by advertising a lot of attractive offers. There is a need for the selection mechanism which accepts the requester's various requirements on business offers to find the most profitable service. In this paper, we identify various business offers of service providers in e-business domain and broadly classify them based on requester's point of view as, unconditional business offers, conditional business offers and probabilistic business offers. We also provide a vocabulary for various business offers of service providers. The paper explores different types of requester's requirements on business offers and proposes a language to express such requirements on various business offers. We propose a tree structure to represent requester's complex business offer requirements for the business offer driven Web service selection.Item Analysis of mobile beacon aided in-range localization scheme in ad hoc wireless sensor networks(2006) Srinath, T.V.; Katti, A.K.; Ananthanarayana, V.S.In this paper, We mathematically model the In-Range localization scheme in the presence of a Mobile Beacon. In the In-Range localization scheme, a sensor with unknown location is localized to a disc centered at the position of the beacon, if the sensor under consideration can successfully decode a transmission from the beacon. In our approach a Mobile Beacon guided by a mobility model is used to generate the virtual beacons, there by eliminating the need to deploy static beacons that are required in the classical In-Range localization scheme. For analysis, we consider a Mobile Beacon guided by the Random Way Point (RWP) mobility model with In-Range localization scheme. The main contribution of this paper consists of mathematical models for the In-Range localization parameters in the presence of a Mobile Beacon guided by the RWP mobility model. Copyright 2006 ACM.Item An expemmental study of the effect of frequency of co-occurrence of features in clustering(2007) Pai, R.M.; Ananthanarayana, V.S.In this paper, an attempt has been made to explore the effect of frequency of co-occurrence of features on the accuracy of the clustering results. This has been achieved by incorporating the frequency component in the clustering algorithm. The frequency, we mean here is the number of times the sequence of features appear in the data set. We try to utilize this component in the algorithm and study its effect on the resultant accuracy. The algorithm we have used is the PC(pattern count)-tree based clustering algorithm. The PC-tree is a compact and complete representation of the data set. It is data order independent and incremental. It can be applied to changing data and changing knowledge. i.e. dynamic databases. This algorithm is based on a compact data structure called PC-tree. The node of the PC-tree has, in addition to other fields a count field, which keeps track of the count of the number of features shared by the pattern. In the literature, the PC-tree was used for clustering and the count field was used only to retrieve back the transactions. In this paper, we try to make use of this field in clustering. We have also used the partitioned PC-tree based algorithm and studied the effect of frequency on the accuracy. We have conducted extensive experiments with the OCR handwritten digit dataset, a real dataset and observed the effect of frequency on the clustering results. The results of all our experiments are tabulated. �2007 IEEE.Item An abstraction based communication efficient distributed association rule mining(2008) Santhi Thilagam, P.; Ananthanarayana, V.S.Association rule mining is one of the most researched areas because of its applicability in various fields. We propose a novel data structure called Sequence Pattern Count, SPC, tree which stores the database compactly and completely and requires only one scan of the database for its construction. The completeness property of the SPC tree with respect to the database makes it more suitable for mining association rules in the context of changing data and changing supports without rebuilding the tree. A performance study shows that SPC tree is efficient and scalable. We also propose a Doubly Logaxithmic-depth Tree, DLT, algorithm which uses SPC tree to efficiently mine the huge amounts of geographically distributed datasets in order to minimize the communication and computation costs. DLT requires only O(n) messages for support count exchange and it takes only O(log log n) time for exchange of messages, which increases its efficiency. � Springer-Verlag Berlin Heidelberg 2008.