This structure data is discoverable by the provision of web structure schema through database techniques for Web pages. This connection allows a search engine to pull data relating to a search query directly to the linking Web page from the Web site the where the content is present. This completion takes place through use of spiders scanning the Web sites, retrieving the home page, then, linking the information through reference links to bring forth the specific page containing the desired
3.3.3 MEAD BASED TECHNIQUE: MEAD  is a centroid-based extractive summarizer that scores sentences based on sentence-level and inter-sentence features which indicates the quality of the sentence as a summary sentence. It then chooses the top-ranked sentences for inclusion in the output summary. MEAD extractive summaries score sentences according to certain sentence features - Centroid, Position, and Length. In this technique the score of a sentence is calculated using the following formula as follows
Text mining is the process of extracting high quality information from unstructured or semi structured data. The high quality information refers to the combination of relevancy and novelty. Figure 2 shows the important process of text mining. Figure 2: Text mining process flow Data Gathering Text mining deals with the unstructured data or semi structured data. The sources of text may be a file, single document, document collection from online and offline both.
Last decade has witnessed many exciting advances in the use of genetic algorithms (GAs) to solve optimization problems in process control systems. Genetic algorithms (GAs) are the solution for optimization of hard problems quickly, reliably and accurately. As the complexity of the real-time controller increases, the genetic algorithms (GAs) applications have grown in more than equal measure. One of the most fundamental principal in our world is the search for an optimal state. Optimization is the process of modifying the inputs or characteristics of a device, mathematical process to obtain minimum or maximum of the output.
2.2.1 Tokenisation In lexical analysis, tokenization is the process of breaking a stream of text up into words, phrases, symbols, or other meaningful elements called tokens. The list of tokens becomes input for further processing such as parsing or text mining. In order to extract keywords, a number of preprocessing steps must be carried out. A piece of text is essentially just a string of characters. This string of characters must be broken up into words.
The genetic algorithm is a heuristic method which is used to improve the solution space for genetic algorithm. The genetic algorithm results in nearest optimal solution within a reasonable time. This paper mainly focuses on various stages of genetic algorithm and comparative study on various methods used for genetic algorithm. The paper also proposes a method to solve the travelling salesman problem and hence improve the solution space. Keywords Travelling Salesman Problem, Genetic Algorithm, Selection, Sequential Constructive Crossover, Mutation I.
Some of technologies utilized in web mapping are spatial databases, tiled web maps, vector tiles and WMS Server. Spatial databases are object relational database which are improved with geographic data and properties. If a web mapping application need to utilize dynamic data; which changes oftenly or to utilize abundant geographic data, the usage of spatial database are needed. Spatial databases allow users perform geometry manipulations, spatial queries, and reprojections. It also provides a variety of import and export formats.
Abstract: Data mining is used to extract the information from the large dataset and used to predict patterns and behavior of an application. Data mining plays a chief role in the fields of e-commerce, healthcare sector, and agricultural sector. Agriculture is the prime occupation in India. Crop productivity mainly depends on weather conditions. Data mining is used in agriculture to predict crop productivity, water management, crop disease management, pesticide recommendation by using different algorithms.
In this context the selection of characteristics and also the influence of domain knowledge and domain-specific procedures play an important role. Therefore, an adaptation of the known data mining algorithms to text data is usually necessary. In order to achieve this, one frequently relies on the experience and results of research in information retrieval, natural language processing and information extraction. In all of these areas we also apply data mining methods and statistics to handle their specific tasks: Information Retrieval (IR): Information retrieval is the finding of documents which contain answers to questions and not the finding of answers itself. In order to achieve this goal statistical measures and methods are used for the automatic processing of text data and comparison to the given question.
Each group will execute local searches seeing to minimize its own set of variables. The current fitness of each member from this group by combining its variables with the best solutions found so far by the remaining groups. The pseudo code for the CGSO algorithm is listed in Table