Top down xml keyword query processing
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The document discusses a new approach to efficiently answer XML keyword queries by proposing a generic top-down processing strategy that addresses common ancestor-repetition (CAR) and visiting useless nodes (VUN) problems. It introduces an inverted index structure called llists, which improves computational efficiency and reduces time complexity compared to existing algorithms. The proposed system supports various query semantics without the inefficiencies present in current methods.
Top down xml keyword query processing
- 1. #13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, Vellore – 6. Off: 0416-2247353 / 6066663 Mo: +91 9500218218 Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com Top-Down Xml Keyword Query Processing ABSTRACT Efficiently answering XML keyword queries has attracted much research effort in the last decade. The key factors resulting in the inefficiency of existing methods are the common ancestor-repetition (CAR) and visiting-useless-nodes (VUN) problems. To address the CAR problem, we propose a generic top-down processing strategy to answer a given keyword query w.r.t. LCA/SLCA/ELCA semantics. By “top-down”, we mean that we visit all common ancestor (CA) nodes in a depth-first, left-to-right order; by “generic”, we mean that our method is independent of the query semantics. To address the VUN problem, we propose to use child nodes, rather than descendant nodes to test the satisfiability of a node v w.r.t. the given semantics. We propose two algorithms that are based on either traditional inverted lists or our newly proposed LLists to improve the overall performance. We further propose several algorithms that are based on hash search to simplify the operation of finding CA nodes from all involved LLists. The experimental results verify the benefits of our methods according to various evaluation metrics. EXISTING SYSTEM Typically, an XML document can be modeled as a node labeled tree T. For a given keyword query Q, several semantics have been proposed to define meaningful results, for which the basic semantics is Lowest Common Ancestor. Based on LCA, the most widely adopted query semantics are Exclusive LCA (ELCA) and Smallest LCA (SLCA). SLCA defines a subset of LCA nodes, of which no LCA is the ancestor of any other LCA. As a comparison, ELCA tries to capture more meaningful results; it may take some LCAs that are not SLCAs as meaningful results. Obviously, a system supporting more query semantics will facilitate users to find interesting results, since any query semantics cannot work well in all situations. However, each of existing algorithms focuses on certain query semantics. Simply implementing them to support all query semantics will result in big index size and make it unscalable to new query semantics, and more importantly, these algorithms are still inefficient due to redundant computation.
- 2. #13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, Vellore – 6. Off: 0416-2247353 / 6066663 Mo: +91 9500218218 Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com DISADVANTAGES OF EXISTING SYSTEM: 1. The existing algorithms are still suffer from redundant computation by visiting many useless components 2. Common-ancestor-repetition problem 3. Visiting useless nodes problem PROPOSED SYSTEM Considering the above problems, we propose to support different query semantics with a generic processing strategy, which is more efficient by avoiding both the CAR and VUN problems, such that to further reduce the number of visited components. To address the CAR problem, we propose a generic top-down XML keyword query processing strategy. To address the VUN problem, we propose to use child nodes, rather than descendant nodes, to test the satisfiability of node v with respect to xLCA semantics. We propose a labeling-scheme- independent inverted index, namely LList, which maintains every node in each level of a traditional inverted list only once and keeps all necessary information for answering a given keyword query without any loss. ADVANTAGES OF PROPOSED SYSTEM: 1. Reduce the time complexity 2. Avoid the CAR and VUN problems 3. Based on LLists, our second top-down algorithm, namely TDxLCA-L, further reduces the time complexity. MODULES 1. LList Index Module 2. Compute CA Nodes Module
- 3. #13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, Vellore – 6. Off: 0416-2247353 / 6066663 Mo: +91 9500218218 Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com MODULE DESCRIPTION: LList Index: Labeling-scheme-independent inverted index (LList), based on this we can reduce both the cost and calling times of binary search operation. Compute CA Nodes: Top-Down Exclusive LCA (TDELCA) recursively gets all CA nodes in a top-down way. For each CA node, it finds out the number of occurrences of each query keyword in its subtree, i.e., the length of each of its child list, and then gets node’s child CA nodes by intersecting node’s child lists using binary search operation. SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS: Processor - Pentium –IV Speed - 1.1 Ghz Ram - 256 Mb Hard Disk - 20 Gb Key Board - Standard Windows Keyboard Mouse - Two or Three Button Mouse Monitor - SVGA SOFTWARE REQUIREMENTS: Operating System - Windows XP Coding Language - Java