Retrieval of structured documents

• US 8,046,370 B2
• Filed: 09/16/2008
• Issued: 10/25/2011
• Est. Priority Date: 01/06/2003
• Status: Active Grant

• Current Assignee: Zhigu Holdings Limited
• Original Assignee: Microsoft Corporation
• Inventors: Cui, Hang, Wen, Ji-Rong
• Primary Examiner(s): Breene; John E
• Assistant Examiner(s): Ly; Anh
• Application Number:
  US12/211,793
• Publication Number:
  US 20090012956A1
• Time in Patent Office: 1,134 Days
• Field of Search: 707/723, 707/730, 707/748, 707/770, 707/811, 707/E17.071, 707/E17.084, 707/E17.122, 707/778, 707/796, 707/797, 715/223, 715/234
• US Class Current: 707/748
• CPC Class Codes: G06F 16/3341 using boolean model
• CPC Class Codes: G06F 16/338 Presentation of query results
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: Y10S 707/956 Hierarchical
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access
• CPC Class Codes: Y10S 707/99936 Pattern matching access
• CPC Class Codes: Y10S 707/99937 Sorting

Abstract

This disclosure relates to performing a query for a search term of a database containing a plurality of structured documents. Those structured documents that do not include the search term are ferreted or filtered out during an initial search. Matched structured documents which are those structured documents that do contain the search term are evaluated by ranking the individual elements based on how well each individual element matches the search term, and indicating to the user the ranking of the individual elements wherein the individual elements can be accessed by the user.

Claims

1. A computer-implemented method, comprising:

under control of one or more computing devices comprising one or more processors,

ranking structured elements within a structured document, the structured document includes a document element or root element, at least one section element, and at least one paragraph elements, the ranking including;

for each paragraph element, in which Weight(t_i, P_j) stands for the weight of the term t_i in the paragraph P_j, “

t_f(t_i, P_j)”

is the term frequency of t_i in this paragraph, N denotes the number of documents in the corpus, and n_i represents the number of documents containing the term t_i, calculating the terms'"'"' weight according to the calculation;

2. The computer-implemented method of claim 1, further comprising indicating to the user the ranking of the individual elements wherein the individual elements can be accessed by the user.

3. The computer-implemented method of claim 2, wherein the indicating to the user includes displaying a hierarchical structure of the matched document to the user.

4. The computer-implemented method of claim 3, wherein the displaying the hierarchical structure includes providing a hierarchical tree that displays the structure of the structured document.

5. The computer-implemented method of claim 1, wherein the ranking of the individual elements is indicated numerically.

6. The computer-implemented method of claim 1, wherein the ranking of the individual elements is indicated by graphic indicators.

7. The computer-implemented method of claim 6, wherein the graphic indicators are asterisks.

8. The computer-implemented method of claim 1, further comprising weighting individual elements, wherein the weighting individual elements includes an entropy measure.