US20190146954A1 - Hierarchical seedlists for application data - Google Patents
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- US20190146954A1 US20190146954A1 US16/243,059 US201916243059A US2019146954A1 US 20190146954 A1 US20190146954 A1 US 20190146954A1 US 201916243059 A US201916243059 A US 201916243059A US 2019146954 A1 US2019146954 A1 US 2019146954A1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/10—File systems; File servers
- G06F16/18—File system types
- G06F16/185—Hierarchical storage management [HSM] systems, e.g. file migration or policies thereof
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/242—Query formulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2455—Query execution
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/26—Visual data mining; Browsing structured data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/282—Hierarchical databases, e.g. IMS, LDAP data stores or Lotus Notes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/31—Indexing; Data structures therefor; Storage structures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/35—Clustering; Classification
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/951—Indexing; Web crawling techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/955—Retrieval from the web using information identifiers, e.g. uniform resource locators [URL]
- G06F16/9566—URL specific, e.g. using aliases, detecting broken or misspelled links
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/958—Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
Definitions
- the present invention relates to the field of content crawling and more particularly to crawling hierarchically structured content sources.
- Search engines generally locate and index content on the World Wide Web and also internally defined networks by parsing content word by word to generate index records correlating the word with a location in a document.
- Internet bots specifically tailored to populate search engine databases commonly are deployed and permitted to “crawl” or “spider” the accessible World Wide Web first locating content, subsequently indexing located content, linking to related content, and repeating the process.
- crawling or spidering the foregoing process forms the foundation of modern search engine technologies.
- a focused crawler seeks, acquires, indexes, and maintains pages on a specific set of topics that represent a relatively small portion of the World Wide Web. Focused crawlers require a much smaller investment in computing resources and can achieve high coverage of pertinent content at a rapid rate.
- a focused crawler usually can begin with a seed list that contains uniform resource locators (URLs) that are relevant to a topic of interest. Subsequently, the focused crawler can crawl the URLs and follow the hyperlinks from the pages corresponding to the URLs to identify the most promising hyper links based upon both the content of the source pages and the hyperlink structure of the World Wide Web.
- URLs uniform resource locators
- the seed list can resemble a site map of relevant content for a topic of interest.
- site maps directly map to a Web site's entry points.
- a seed list seeks to directly represent content at the application level which differs from the organization of the content at the Web site level.
- seed lists mirror application structure and present a hierarchical representation of content as the application originally intended it to be, and not necessarily as a Web site would present the content.
- Embodiments of the present invention address deficiencies of the art in respect to crawling content and provide a novel and non-obvious method, system and computer program product for seed lists for hierarchically structured content sources.
- a method for crawling seed lists for hierarchically structured content sources can be provided. The method can include specifying a depth of crawling for hierarchically structured content, crawling only seed lists at the specified depth among other seed lists in a hierarchy of seed lists mimicking the hierarchically structured content, and returning indexed data for the crawled seed lists.
- an administrator user interface can be provided for specifying the depth of crawling for the hierarchically structured content.
- a content distribution data processing system can be provided.
- the system can include hierarchically structured content, a hierarchy of seed lists mimicking the hierarchically structured content, a seed list crawler, and hierarchical seed list browsing logic.
- the logic can include program code enabled to specify a depth of crawling for the hierarchically structured content, to crawl only seed lists at the specified depth among other seed lists in the hierarchy of seed lists, and to return indexed data for the crawled seed lists.
- an administrator user interface can be configured to specify the depth of crawling.
- FIG. 1 is a schematic illustration of a content distribution data processing system configured for seed lists for hierarchically structured content sources;
- FIG. 2 is a flow chart illustrating a process for crawling seed lists for hierarchically structured content sources.
- Embodiments of the present invention provide a method, system and computer program product for crawling seed lists for hierarchically structured content sources.
- a seed list for a hierarchically structured content source can be extended to reference other seed lists to mimic the hierarchy of the hierarchically structured content source.
- Referenced seed lists optionally can reference yet other seed lists and so forth in establishing a hierarchy of seed lists.
- a crawler can crawl any portion of the extended seed list at any depth of the hierarchy by selectively initiating crawling content at any hierarchical level of seed lists defined for the extended seed list.
- content can be crawled and indexed at any depth of the hierarchy reflected by the extended seed list.
- FIG. 1 schematically depicts a content distribution data processing system configured for seed lists for hierarchically structured content sources.
- the system can include a host computing platform 130 supporting the operation of an application 160 managing hierarchically structured content 170 .
- the host computing platform 130 can be communicatively coupled to a computer communications network 120 , for example the global Internet.
- the system also can include a seed list crawler 150 operating in a host computing platform 110 also communicatively coupled to the computer communications network 120 .
- the seed list crawler 150 can be configured to crawl the hierarchically structured content 170 by reference to a corresponding seed list 100 A and by creating a search index 140 for crawled content referenced in the seed list 100 A.
- the seed list 100 A can be extended to reference other seed lists 100 B in addition to content.
- the hierarchy 100 formed by the seed list 100 A and its referenced seed lists 100 B can mimic the hierarchically structured content 170 of the application 160 .
- a representative form of the seed list 100 A can include:
- a representative form of a seed list 100 A can reference content as follows:
- hierarchical seed list browsing logic 190 can be coupled to the seed list crawler 150 .
- the hierarchical seed list browsing logic 190 can include program code enabled selectively crawl and index the hierarchically structured content by reference to the seed list 100 A and its referenced seed lists 100 B.
- indexed data 180 can be retrieved by the logic 190 for selected portions of the hierarchically structured content 170 by processing only selected ones of the seed lists 100 B.
- the logic 190 can specify to only collect indexed data 180 for content at or below a particular depth of the hierarchy 100 by processing content and corresponding seed lists 100 B at or below the specified depth. Likewise, the logic 190 can specify to only collect indexed data 180 for content at a particular depth of the hierarchy 100 by processing content and corresponding seed lists 100 B at the specified depth. Yet further, the logic 190 can specify to collect indexed data 180 for content at all depths of the hierarchy 100 by processing content and corresponding seed lists 100 A, 100 B at all depths of the hierarchy 100 . Crawling directives for collecting indexed data 180 can be specified through an administration user interface presenting the hierarchy 100 of seed lists 100 A, 100 B.
- FIG. 2 is a flow chart illustrating a process for crawling seed lists for hierarchically structured content sources.
- the process can begin in block 210 in which a crawl request can be received.
- an initial depth of crawling can be established for the hierarchy of seed lists and in block 230 , a seed list can be retrieved from within the hierarchy of seed lists.
- the entire hierarchy of seed lists can be crawled.
- a seed list at the specified depth can be selected, crawled and its content indexed according to the seed list.
- decision block 250 it can be determined if sub-seed lists appear within the selected seed list. If so, in decision block 260 it further can be determined whether the sub-seed lists of the selected speed list are to be aggregated, or whether the sub-seed lists are to be processed separately.
- decision block 260 if it is determined that the sub-seed lists are to be processed separately, in block 290 the selected depth can be increased to account for the sub-speed lists and the process can continue through block 280 with the selection of the speed lists at the specified depth and with the crawling and indexing of the sub-speed lists in block 240 . Where no sub-speed lists are present in the selected speed list, or where the sub-speed lists for the selected speed list are to be aggregated, in decision block 270 it can be determined if additional speed lists remain to be processed. If so, the process can continue in block 280 with the selection of a next speed list at the specified depth. When no speed lists remain to be processed, in block 300 the index can be returned to the requestor.
- Embodiments of the invention can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment containing both hardware and software elements.
- the invention is implemented in software, which includes but is not limited to firmware, resident software, microcode, and the like.
- the invention can take the form of a computer program product accessible from a computer-usable or computer-readable medium providing program code for use by or in connection with a computer or any instruction execution system.
- a computer-usable or computer readable medium can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
- the medium can be an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system (or apparatus or device) or a propagation medium.
- Examples of a computer-readable medium include a semiconductor or solid state memory, magnetic tape, a removable computer diskette, a random access memory (RAM), a read-only memory (ROM), a rigid magnetic disk and an optical disk.
- Current examples of optical disks include compact disk-read only memory (CD-ROM), compact disk-read/write (CD-R/W) and DVD.
- a data processing system suitable for storing and/or executing program code will include at least one processor coupled directly or indirectly to memory elements through a system bus.
- the memory elements can include local memory employed during actual execution of the program code, bulk storage, and cache memories which provide temporary storage of at least some program code in order to reduce the number of times code must be retrieved from bulk storage during execution.
- I/O devices including but not limited to keyboards, displays, pointing devices, etc.
- Network adapters may also be coupled to the system to enable the data processing system to become coupled to other data processing systems or remote printers or storage devices through intervening private or public networks. Modems, cable modem and Ethernet cards are just a few of the currently available types of network adapters.
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Abstract
Description
- The present invention relates to the field of content crawling and more particularly to crawling hierarchically structured content sources.
- The development of the modern computer communications network and the wide-scale adoption of the global Internet as a primary source of information have transformed the way in which information is both generated and also shared amongst individuals. Prior to electronic methods of publishing content, individuals seeking information largely relied upon libraries and personal subscriptions to periodicals, newspapers and journals. By comparison, today one can access vast repositories of data in a matter of minutes that otherwise would consume hours if not days of tedious, manual scouring of print documents.
- Even before the popularization of the World Wide Web, information technologists recognized the need to properly index electronic content such that the content can be accessed electronically and remotely by interested parties. Indeed, the very need to access related content led to the development of the hyperlink and markup language formatted documents both of which enabled the acceptance of the World Wide Web. The World Wide Web itself can be viewed as a vast hierarchy of related documents and content, connected through hyperlink relationships all of which can be accessed globally over the Internet. From the very beginning, search engine technologies evolved to address the need to discover and catalog content published and accessible through the World Wide Web.
- Search engines generally locate and index content on the World Wide Web and also internally defined networks by parsing content word by word to generate index records correlating the word with a location in a document. In order to automate the discover of available content on the World Wide Web, Internet bots specifically tailored to populate search engine databases commonly are deployed and permitted to “crawl” or “spider” the accessible World Wide Web first locating content, subsequently indexing located content, linking to related content, and repeating the process. Known as crawling or spidering, the foregoing process forms the foundation of modern search engine technologies.
- Unlike a general, content crawler, a focused crawler seeks, acquires, indexes, and maintains pages on a specific set of topics that represent a relatively small portion of the World Wide Web. Focused crawlers require a much smaller investment in computing resources and can achieve high coverage of pertinent content at a rapid rate. A focused crawler usually can begin with a seed list that contains uniform resource locators (URLs) that are relevant to a topic of interest. Subsequently, the focused crawler can crawl the URLs and follow the hyperlinks from the pages corresponding to the URLs to identify the most promising hyper links based upon both the content of the source pages and the hyperlink structure of the World Wide Web.
- The seed list, then, can resemble a site map of relevant content for a topic of interest. In this regard, site maps directly map to a Web site's entry points. In contrast, a seed list seeks to directly represent content at the application level which differs from the organization of the content at the Web site level. To do this effectively, seed lists mirror application structure and present a hierarchical representation of content as the application originally intended it to be, and not necessarily as a Web site would present the content. Moreover, in a conventional seed list, one must choose either to crawl the entire seed list, or to omit consideration of the seed list. Accordingly, the use of a seed list with a focused crawler does not comport with the hierarchical nature of application data.
- Embodiments of the present invention address deficiencies of the art in respect to crawling content and provide a novel and non-obvious method, system and computer program product for seed lists for hierarchically structured content sources. In one embodiment, a method for crawling seed lists for hierarchically structured content sources can be provided. The method can include specifying a depth of crawling for hierarchically structured content, crawling only seed lists at the specified depth among other seed lists in a hierarchy of seed lists mimicking the hierarchically structured content, and returning indexed data for the crawled seed lists. Optionally, an administrator user interface can be provided for specifying the depth of crawling for the hierarchically structured content.
- In another embodiment of the invention, a content distribution data processing system can be provided. The system can include hierarchically structured content, a hierarchy of seed lists mimicking the hierarchically structured content, a seed list crawler, and hierarchical seed list browsing logic. The logic can include program code enabled to specify a depth of crawling for the hierarchically structured content, to crawl only seed lists at the specified depth among other seed lists in the hierarchy of seed lists, and to return indexed data for the crawled seed lists. Optionally, an administrator user interface can be configured to specify the depth of crawling.
- Additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The aspects of the invention will be realized and attained by means of the elements and combinations particularly pointed out in the appended claims. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
- The accompanying drawings, which are incorporated in and constitute part of this specification, illustrate embodiments of the invention and together with the description, serve to explain the principles of the invention. The embodiments illustrated herein are presently preferred, it being understood, however, that the invention is not limited to the precise arrangements and instrumentalities shown, wherein:
-
FIG. 1 is a schematic illustration of a content distribution data processing system configured for seed lists for hierarchically structured content sources; and, -
FIG. 2 is a flow chart illustrating a process for crawling seed lists for hierarchically structured content sources. - Embodiments of the present invention provide a method, system and computer program product for crawling seed lists for hierarchically structured content sources. In accordance with an embodiment of the present invention, a seed list for a hierarchically structured content source can be extended to reference other seed lists to mimic the hierarchy of the hierarchically structured content source. Referenced seed lists optionally can reference yet other seed lists and so forth in establishing a hierarchy of seed lists. Thereafter, a crawler can crawl any portion of the extended seed list at any depth of the hierarchy by selectively initiating crawling content at any hierarchical level of seed lists defined for the extended seed list. Thus, content can be crawled and indexed at any depth of the hierarchy reflected by the extended seed list.
- In illustration,
FIG. 1 schematically depicts a content distribution data processing system configured for seed lists for hierarchically structured content sources. The system can include ahost computing platform 130 supporting the operation of anapplication 160 managing hierarchically structuredcontent 170. Thehost computing platform 130 can be communicatively coupled to acomputer communications network 120, for example the global Internet. The system also can include aseed list crawler 150 operating in ahost computing platform 110 also communicatively coupled to thecomputer communications network 120. Theseed list crawler 150 can be configured to crawl the hierarchically structuredcontent 170 by reference to acorresponding seed list 100A and by creating asearch index 140 for crawled content referenced in theseed list 100A. - Notably, the
seed list 100A can be extended to referenceother seed lists 100B in addition to content. In this regard, thehierarchy 100 formed by theseed list 100A and its referencedseed lists 100B can mimic the hierarchically structuredcontent 170 of theapplication 160. In illustration, a representative form of theseed list 100A can include: -
<?xml version=″1.0″ encoding=″utf-8″?> <feed xmlns=″http://www.w3.org/2005/Atom″> <title>Feed representing SubSeedlists</title> <link href=″http://example.org/″/> <updated>2003-12-13T18:30:02Z</updated> <author> <name>John Doe</name> </author> <id>urn:uuid:60a76c80-d399-11d9-b93C-0003939e0af6</id> <entry> <title>SubSeedlistWithNoEntries</title> <link href=″http://example.org/2003/12/13/atom03″ rel=″child″/> <id>urn:uuid:1225c695-cfb8-4ebb-aaaa-80da344efa6a</id> <updated>2003-12-13T18:30:02Z</updated> <summary>Subseedlist with no content</summary> </entry> <entry> <title>SubSeedlistWithEntries</title> <link href=http://example.org/2003/12/13/atom03 ″ rel=″child” /> <id>urn:uuid:1225c695-cfb8-4ebb-aaaa-80da344efa6a</id> <updated>2003-12-13T18:30:02Z</updated> <content type=″text″ xml:lang=″en″ src=″ http://example.org/AtomFeedContainingEntries.xml″ </content> <summary> Subseedlist that has contents.</summary> </entry> </feed> - As an alternative, a representative form of a
seed list 100A can reference content as follows: -
<?xml version=“1.0” encoding=“utf-8”?> <feed xmlns=“http://www.w3.org/2005/Atom”> <title>Seedlist which can return content</title> <link href=“http://example.org/”/> <updated>2003-12-13T18:30:02Z</updated> <author> <name>John Doe</name> </author> <id>urn:uuid:60a76c80-d399-11d9-b93C-0003939e0af6</id> <entry> <title>Document1</title> <link href=“http://example.org/Document1.html” rel=“via”/> <id>urn:uuid:1225c695-cfb8-4ebb-aaaa-80da344efa6a</id> <content type=“text” xml:lang=“en” src=“ http://example.org/Document1.html” <updated>2003-12-13T18:30:02Z</updated> <summary>Document 1 summary.</summary> </entry> <entry> <title>Document2</title> <link href=“” rel=“via”/> <id>urn:uuid:1225c695-cfb8-4ebb-aaaa-80da344efa6a</id> <content type=“text” xml:lang=“en” src=“ http://example.org/Document2.html” <updated>2003-12-13T18:30:02Z</updated> <summary>Document 2 summary.</summary> </entry> - As shown in
FIG. 1 , hierarchical seedlist browsing logic 190 can be coupled to theseed list crawler 150. The hierarchical seedlist browsing logic 190 can include program code enabled selectively crawl and index the hierarchically structured content by reference to theseed list 100A and its referenced seed lists 100B. In particular, indexeddata 180 can be retrieved by thelogic 190 for selected portions of the hierarchically structuredcontent 170 by processing only selected ones of the seed lists 100B. - For example, the
logic 190 can specify to only collect indexeddata 180 for content at or below a particular depth of thehierarchy 100 by processing content and corresponding seed lists 100B at or below the specified depth. Likewise, thelogic 190 can specify to only collect indexeddata 180 for content at a particular depth of thehierarchy 100 by processing content and corresponding seed lists 100B at the specified depth. Yet further, thelogic 190 can specify to collect indexeddata 180 for content at all depths of thehierarchy 100 by processing content and corresponding seed lists 100A, 100B at all depths of thehierarchy 100. Crawling directives for collecting indexeddata 180 can be specified through an administration user interface presenting thehierarchy 100 of seed lists 100A, 100B. - In further illustration,
FIG. 2 is a flow chart illustrating a process for crawling seed lists for hierarchically structured content sources. The process can begin inblock 210 in which a crawl request can be received. Inblock 220, an initial depth of crawling can be established for the hierarchy of seed lists and inblock 230, a seed list can be retrieved from within the hierarchy of seed lists. In particular, to the extent that the initial depth of the hierarchy is set to root, the entire hierarchy of seed lists can be crawled. In any event, inblock 240, a seed list at the specified depth can be selected, crawled and its content indexed according to the seed list. Thereafter, indecision block 250 it can be determined if sub-seed lists appear within the selected seed list. If so, indecision block 260 it further can be determined whether the sub-seed lists of the selected speed list are to be aggregated, or whether the sub-seed lists are to be processed separately. - In
decision block 260, if it is determined that the sub-seed lists are to be processed separately, inblock 290 the selected depth can be increased to account for the sub-speed lists and the process can continue throughblock 280 with the selection of the speed lists at the specified depth and with the crawling and indexing of the sub-speed lists inblock 240. Where no sub-speed lists are present in the selected speed list, or where the sub-speed lists for the selected speed list are to be aggregated, indecision block 270 it can be determined if additional speed lists remain to be processed. If so, the process can continue inblock 280 with the selection of a next speed list at the specified depth. When no speed lists remain to be processed, inblock 300 the index can be returned to the requestor. - Embodiments of the invention can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment containing both hardware and software elements. In a preferred embodiment, the invention is implemented in software, which includes but is not limited to firmware, resident software, microcode, and the like. Furthermore, the invention can take the form of a computer program product accessible from a computer-usable or computer-readable medium providing program code for use by or in connection with a computer or any instruction execution system.
- For the purposes of this description, a computer-usable or computer readable medium can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The medium can be an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system (or apparatus or device) or a propagation medium. Examples of a computer-readable medium include a semiconductor or solid state memory, magnetic tape, a removable computer diskette, a random access memory (RAM), a read-only memory (ROM), a rigid magnetic disk and an optical disk. Current examples of optical disks include compact disk-read only memory (CD-ROM), compact disk-read/write (CD-R/W) and DVD.
- A data processing system suitable for storing and/or executing program code will include at least one processor coupled directly or indirectly to memory elements through a system bus. The memory elements can include local memory employed during actual execution of the program code, bulk storage, and cache memories which provide temporary storage of at least some program code in order to reduce the number of times code must be retrieved from bulk storage during execution. Input/output or I/O devices (including but not limited to keyboards, displays, pointing devices, etc.) can be coupled to the system either directly or through intervening I/O controllers. Network adapters may also be coupled to the system to enable the data processing system to become coupled to other data processing systems or remote printers or storage devices through intervening private or public networks. Modems, cable modem and Ethernet cards are just a few of the currently available types of network adapters.
Claims (10)
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US8601003B2 (en) * | 2008-09-08 | 2013-12-03 | Apple Inc. | System and method for playlist generation based on similarity data |
CN111125482B (en) * | 2018-10-31 | 2023-04-07 | 北京国双科技有限公司 | Method and device for adjusting data crawling frequency, storage medium and processor |
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US10176258B2 (en) * | 2007-06-28 | 2019-01-08 | International Business Machines Corporation | Hierarchical seedlists for application data |
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