a)Web mining is the integration of information gathered by traditional data mining methodologies and techniques with information gathered over the World Wide Web. (Mining means extracting something useful or valuable from a baser substance, such as mining gold from the earth.)
b)Association rule mining is a procedure which is meant to find frequent patterns, correlations, associations, or causal structures from data sets found in various kinds of databases such as relational databases, transactional databases, and other forms of data repositories. 
c)Web preprocessing includes data cleaning, data integration, data transformation and data reduction. Data cleaning is aimed to remove unrelated or redundant items.
d) Web content mining is the process of extracting useful information from the web documents. It contains the generation of wrappers. Wrapper is a set of extraction rules to extract the data from the web pages
Ans 2  a) 

b) Support Vector Machine (SVM) is primarily a classier method that performs classification tasks by constructing hyperplanes in a multidimensional space that separates cases of different class labels. SVM supports both regression and classification tasks and can handle multiple continuous and categorical variables. For categorical variables a dummy variable is created with case values as either 0 or 1. Thus, a categorical dependent variable consisting of three levels, say (A, B, C), is represented by a set of three dummy variables:
A: {1 0 0}, B: {0 1 0}, C: {0 0 1}
Ans 3. a) An information retrieval system is a software programme that stores and manages information on documents, often textual documents but possibly multimedia.The system assists users in finding the information they need. It does not explicitly return information or answer questions. Instead, it informs on the existence and location of documents that might contain the desired information. Some suggested documents will, hopefully, satisfy the user’s information need. These documents are called relevant documents. A perfect retrieval system would retrieve only the relevant documents and no irrelevant documents. There are three basic processes an information retrieval system has to support the representation of the content of the documents, the representation of the user’s information need, and the comparison of the two representations.

b) The task of sequential pattern mining is a data mining task specialized for analyzing sequential data, to discover sequential patterns. More precisely, it consists of discovering interesting subsequences in a set of sequences, where the interestingness of a subsequence can be measured in terms of various criteria such as its occurrence frequency, length, and profit.
 Sequential pattern mining has numerous real-life applications due to the fact that data is naturally encoded as sequences of symbols in many fields such as bioinformatics, e-learning, market basket analysis, texts, and  webpage click-stream analysis.Traditionally, sequential pattern mining is being used to find subsequences that appear often in a sequence database, i.e. that are common to several sequences. Those subsequences are called the frequent sequential patterns.To do sequential pattern mining, a user must provide a sequence database and specify a parameter called the minimum support threshold