Search engine using indexing method for storing and...

Data processing: database and file management or data structures – Database design – Data structure types

Reexamination Certificate

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Details

C707S793000, C707S793000, C707S793000, C707S793000, C707S793000

Reexamination Certificate

active

06278992

ABSTRACT:

BACKGROUND AND SUMMARY OF THE INVENTION
The present invention relates to the field of storing and retrieving computerized data through the use of a Search Engine and, more particularly, to the indexing of data in system(s) as it relates to Internet, the World Wide Web, an intranet of local systems and/or any combination thereof. Computers are widely used to store and retrieve information. If the number of stored records is of any significant size, the records are typically stored in a computer database. Given a collection of multiple systems, a Search Engine may be used to locate, find, compare, and track data as it relates to documents (including files, images, objects, programs and other data in various forms referred herein as a document) in the System(s). The Search Engine can read the documents through program(s) commonly referred to as a Web-walker, Web-crawler, Spider, Browser or Robot, which acts similar to a user and notes the words in a document, the words sequence and the size of the document If changes have occurred from a prior scan of the document, the date of the document, the file name, computer or server containing the document, the directory of the document, whether the document has a URL (universal record locator) pictures, objects (video, sound, etc.), attributes (color, font, etc.) links to other documents, meta-tags and any other attribute (spread sheets, graphs, computer code, programs, addresses of other documents and their associated attributes, etc.) that could be placed in or relate to the document.
Present Search Engines such as Google, Excite, and Alta Vista perform these following common functions:
browsing of the documents by a program or system of programs to scan the documents for content and attributes;
parsing of the documents to separate out words, information and attributes;
indexing some or all of the words, information and attributes of the documents into a database;
querying the index and database through a user interface (for live users and/or programs and systems) through local and remote access;
maintaining the information, words and attributes in an index and database through data movement and management programs, as well as re-scanning the systems for documents, looking for changed documents, deleted documents, added documents, moved documents and new systems, files, information, connections to other systems and any other data and information.
Google represents a typical Search Engine. The Internet currently contains over one hundred million documents—each on average containing over 100 unique words with an average of over one unique word per document (the URL is usually also unique). This results in an extremely large database of words (over 100 million) and over 10 billion entries in a database that tracks words in referenced documents. As the Internet grows to more than a billion documents, these databases will grow respectively. In typical Internet Search Engine designs, Hash techniques, B-tree Indexes, sorted lists, and variations thereon are the accepted approaches.
The B-tree approach is one approach to an index and a database. Due to the enormous size of the database, and given changes and growth, the present invention utilizes a new approach for structuring databases for Search Engines. The Search Engine of the present invention uses an indexing method that provides advantages to organizing the tremendous amount of information on the Internet and for searching such information in a fast and efficient process. As discussed in more detail in the following detailed description, the Search Engine of the present invention using the described indexing method provides significant practical advantages over known Search Engines.
For example, the present invention significantly increases the speed with which database records can be stored and retrieved. The present invention increases data retrieval as a function of unique and efficient programming steps rather than through hardware configuration.
In recent years the term database has been used rather loosely, and as a result, has lost some of its usefulness. To some a database is just a collection of data items. Others define the term more strictly. However, for the purposes of the present invention, a database is a self-describing collection of integrated records. A database is self-describing in that it contains a description of its own structure. This is called meta-data. The database is integrated in that it includes the relationships among data items as well as the data items themselves. Accordingly, the term database as used in the present application is not limited to merely bits of stored data or information.
A database is made up of both data and meta-data. Meta-data is data about the structure of the data in a database. This meta-data is stored in a part of the database called the data dictionary, which describes the tables, columns, indexes, constraints, and other items that make up the database.
Databases come in all sizes, from a simple collection of a few records to millions of records. A personal database is designed for use by a single person on a single computer. It tends to be rather simple in structure and small in size. A database is a structure that holds data. The database is structured to operate on the data contained within it.
There are many database management systems (DBMS) on the market today. Some run only on mainframe computers, some only on minicomputers, and some only on personal computers and some on most systems. However, there is a strong trend for such products to work on multiple platforms or on networks that contain all three classes of machines. A database that will run on different operating systems such as OS/2, Windows 3.1, Windows 95, or UNIX are said to be portable. Databases are also scalable if they can make use of adding/removing computers for more or less processing speed or power.
Regardless of the size of the computer that hosts the database, and regardless of whether it is connected to a network, the flow of information between the database and the user is the same. The DBMS mask the physical details of the storage so that the application only has to know about the logical characteristics of the data, not how it is stored.
Database structure makes it possible to interpret seemingly meaningless data. The structure brings to the surface patterns, trends, and tendencies in the data. Unstructured data, like uncombined atoms, has little or no value.
Databases may vary in size and structure. However, they are generally structured as a hierarchical, network, or relational model. The hierarchical database assigns different types of data to different levels of a data structure. The links between the data item on one level and data items on a different level are simple and direct. A major advantage of the hierarchical model is the simplicity of the relationships among data items. However, its rigid structure is a disadvantage.
The opposite of a hierarchical structure is one in which any node has direct access to any other. There is no need to duplicate nodes since they are all universally accessible. The network model is based on this concept.
The relational database model was first formulated by E. F. Codd of IBM in 1970, and started appearing in products about a decade later. Relational databases have attributes that distinguish them from databases built according to other models. In a relational database, the database structure can be changed without requiring changes to applications that were based on the earlier structure. For example, if one or more new columns are added to a database table, older applications that processed the table would not require alteration because the columns they deal with are unaltered.
As discussed, a database is usually more than a collection of tables. Additional structures, on several levels, help maintain the integrity of the data. A database's schema provides an overall organization to the tables. The domain of a table column tells us what values may be stored in the column. You can apply constraint

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