Seasonal variation in the physico-chemical properties of Rushikulya estuary and its effect on the occurrence of Chanos fry

Seasonal variation in some physico-chemical properties of Rushikulya estuary was studied. The surface water temperature varied from 20 to 34.5 degree C, the transparency of the water from 6.3 to 12 cm, the salinity from 28.3 to 32.8 % and the pH from 6.77 to 7.35. The transparency and salinity showed bimodal distribution. Occurrence of the Chanos fry were correlated to it

Web Caching and Prefetching with Cyclic Model Analysis of Web Object Sequences

Web caching is the process in which web objects are temporarily stored to reduce bandwidth consumption, server load and latency. Web prefetching is the process of fetching web objects from the server before they are actually requested by the client. Integration of caching and prefetching can be very beneficial as the two techniques can support each other. By implementing this integrated scheme in a client-side proxy, the perceived latency can be reduced for not one but many users. In this paper, we propose a new integrated caching and prefetching policy called the WCP-CMA which makes use of a profit-driven caching policy that takes into account the periodicity and cyclic behaviour of the web access sequences for deriving prefetching rules. Our experimental results have shown a 10%-15% increase in the hit ratios of the cached objects and 5%-10% decrease in delay compared to the existing schem

Automatic Discovery and Ranking of Synonyms for Search Keywords in the Web

Search engines are an indispensable part of a web user's life. A vast majority of these web users experience difficulties caused by the keyword-based search engines such as inaccurate results for queries and irrelevant URLs even though the given keyword is present in them. Also, relevant URLs may be lost as they may have the synonym of the keyword and not the original one. This condition is known as the polysemy problem. To alleviate these problems, we propose an algorithm called automatic discovery and ranking of synonyms for search keywords in the web (ADRS). The proposed method generates a list of candidate synonyms for individual keywords by employing the relevance factor of the URLs associated with the synonyms. Then, ranking of these candidate synonyms is done using co-occurrence frequencies and various page count-based measures. One of the major advantages of our algorithm is that it is highly scalable which makes it applicable to online data on the dynamic, domain-independent and unstructured World Wide Web. The experimental results show that the best results are obtained using the proposed algorithm with WebJaccard

Similarity based dynamic web data extraction and integration system from search engine result pages for web content mining

There is an explosive growth of information in the World Wide Web thus posing a challenge to Web users to extract essential knowledge from the Web. Search engines help us to narrow down the search in the form of Search Engine Result Pages (SERP). Web Content Mining is one of the techniques that help users to extract useful information from these SERPs. In this paper, we propose two similarity based mechanisms; WDES, to extract desired SERPs and store them in the local depository for offline browsing and WDICS, to integrate the requested contents and enable the user to perform the intended analysis and extract the desired information. Our experimental results show that WDES and WDICS outperform DEPTA [1] in terms of Precision and Recall

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PMEM: Predicting multiple time series using ensemble model

Forecasting Multiple Time Series (MTS) consists of multiple time series with no relation between them and independent of each other. Predicting each time series independently may lead to increase in time and cost. In this paper, we formalize the problem of predicting the multiple time series together over a MTS database. The proposed framework addresses the following issues. First, it build the initial ensemble model for each time series by using a novel Ensemble approach thereby effectively reduce the data storage and time complexity, secondly, by using single ensemble engine for MTS we perform the three major task, i.e., the task of prediction, building new model, ensemble update and lastly predicting the samples by pattern sequence matching using well known Sliding window method. The computational cost for PMEM is O(C * N * (K+ nmatches)) where, nmatches is the Average number of patterns matched

Similarity based web data extraction and integration system for web content mining

The Internet is a major source of all information that we essentially need. The information on the web cannot be analyzed and queried as per the user requests. Here, we propose and develop a similarity based web data extraction and integration system (WDES and WDICS) to extract search result pages from the web and integrate its contents to enable the user to perform intended analysis. The system provides for local replication of search result pages, in a manner convenient for offline browsing. The system organizes itself into two possible phases that are involved in performing the above task. We develop and implement algorithms for extracting and integrating the content from the web. Experiment is performed on the contents of Bluetooth product listings and it gives us a better Precision and Recall than DEPTA 1. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering