Data processing: database and file management or data structures – Database design – Data structure types
Reexamination Certificate
1999-04-06
2001-08-28
Lintz, Paul R. (Department: 2171)
Data processing: database and file management or data structures
Database design
Data structure types
C707S793000, C707S793000
Reexamination Certificate
active
06282537
ABSTRACT:
TECHNICAL FIELD
The present invention relates to retrieving data from heterogeneous data sources including structured sources and semi-structured sources and, more particularly, extracting data from World Wide Web pages in response to a query phrased in a structured query language.
BACKGROUND INFORMATION
The World Wide Web (WWW) is a collection of Hypertext Mark-Up Language (HTML) documents resident on computers that are distributed over the Internet. The WWW has become a vast repository for knowledge. Web pages exist which provide information spanning the realm of human knowledge from information on foreign countries to information about the community in which one lives. The number of Web pages providing information over the Internet has increased exponentially since the World Wide Web's inception in 1990. Multiple Web pages are sometimes linked together to form a Web site, which is a collection of Web pages devoted to a particular topic or theme.
Accordingly, the collection of existing and future World Wide Web pages represents one of the largest databases in the world. However, access to the data residing on individual Web pages is hindered by the fact that World Wide Web pages are not a structured source of data. That is, there is no defined “structure” for organizing information provided by the Web page, as there is in traditional, relational databases. For example, different Web pages may provide the same geographic information about a particular country, but the information may appear in various locations of each page and may be organized differently from page to page. One particular example of this is that one Web site may provide relevant information on one Web page, i.e. in one HTML document, while another Web site may provide the same information distributed over multiple, interrelated Web pages.
A further difficulty associated with retrieving data from the Word Wide Web is that the Web is “document centric” rather than “data centric”. This means that a user is assumed to be looking for a document, rather than an answer. For example, a user seeking the temperature of the Greek Isles during the month of March would be directed to documents dealing with the Greek Isles. Many of those documents might simply contain the words “March,” “Greek,” and “temperature” but otherwise be utterly devoid of temperature information, for example, “the temperature during the day is pleasant in March, especially if one is visiting the Greek Isles.” These documents are useless to the requesting user, however, current techniques of accessing the Web cannot distinguish useless “near-hits” from useful documents. Further, the user is seeking an “answer” (e.g. 65° F.) to a particular question, and not a list of documents that may or may not contain the answer the user is seeking.
Another difficulty associated with extracting data from Web pages is that each Web page potentially provides data in a different format from other Web pages dealing with the same topic or in a different context from the request itself. For example, one Web page may provide a particular value in degrees Centigrade, while another World Wide Web page, or the user seeking the information, may expect that same information to be in degrees Fahrenheit. A requesting system or user would be misled or confused by an answer returned in degrees Centigrade because the requester and the data source do not share the same assumptions about the provision of data values.
These problems are not limited to retrieving data from HTML documents distributed over the Internet. Larger organizations have begun building “intranets”, which are collections of linked HTML documents internal to the organization. While “intranets” are intended to provide a member of an organization with easy access to information about the organization, the problems discussed above with respect the WWW apply to “intranets”. Requiring members of the organization to learn the data context of each Web page, or requiring them to learn a specialized query language for accessing Web pages, would defeat the purpose of the “intranet” and would be virtually impossible on the Internet.
SUMMARY OF THE INVENTION
The present invention allows semi-structured data sources to be queried using a structured query language. This allows semi-structured data sources, such as World Wide Web pages (HTML documents), flat files containing data (data files containing collections of data that are not arranged as a relational database), or menu-driven database systems (sometimes referred to as “legacy” systems) to augment traditional, structured databases without requiring the requester to learn a new, separate query language. Structured queries directed to semi-structured sources are identified, converted into commands the semi-structured data sources understand, and the commands are issued to the data source. Data is extracted from the semi-structured data source and returned to the requester. Thus, semi-structured data sources can be accessed using a structured query language in a way that is transparent to the requester.
A system according to the invention queries both structured and semi-structured data sources. The system includes a request translator, a query converter, a command transmitter, a data retriever, and a data translator. The request translator receives a data request which has an associated data context and translates that data request into a query which has an associated data context which is appropriate for the data source to be queried. The query converter converts at least a portion of the query into a command or series of commands that can be used to interact with a semi-structured data source such as a Web page or a flat file containing data. The command transmitter issues those commands to the semi-structured data sources, and a data retriever extracts data from the data sources. Extracted data is translated by the data translator from the data context of the data source into the data context associated with the initial request.
A method according to the invention queries both structured and semi-structured data sources. The method includes translating a data request into a query, converting at least a portion of the query into a stream of commands, issuing the commands to the semi-structured data sources, extracting data from the data sources, and translating the retrieved data. The data request, which has an associated data context, is translated into the query which has a data context that matches the data source to be queried. At least a portion of that query is converted into one or more commands which can be used to interact with a semi-structured data source. Those commands are issued and data is extracted from the data source. Extracted data is then translated from the data context associated with the data source into the data context associated with the initial request.
In other aspects of the invention, a method and system for querying semi-structured data sources in response to a structured data request comprise the steps of, and means for, converting the data request into one or more commands, issuing the commands to a semi-structured data source, and extracting data from the semi-structured data source. The semi-structured data source can be a World Wide Web page, a flat file containing data, or a menu-driven database system. In some embodiments, the conversion of the data request into one or more commands also includes determining if the requested data is provided by a Web page and then determining, for each requested datum provided by the Web page, one or more commands to issue to the Web page in order to retrieve the data. These determinations are made by accessing a file which is stored in a memory element of a computer and which includes information on the data elements provided by the data source as well as the commands necessary to access the data.
REFERENCES:
patent: 4714995 (1987-12-01), Materna et al.
patent: 5278978 (1994-01-01), Demers et al.
patent: 5345586 (1994-09-01), Hamala et al.
patent: 5416917 (1995-05-01), Adair et al.
patent
Madnick Stuart E.
Siegel Michael D.
Lintz Paul R.
Massachusetts Institute of Technology
Testa Hurwitz & Thibeault LLP
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