Source: http://www.google.com/patents/US6098064?dq=georgia+pacific+dispenser&ei=3350T6jaCc-q0AHQucGAAw
Timestamp: 2017-08-24 05:56:40
Document Index: 124230898

Matched Legal Cases: ['Application No. 08', 'Application No. 08', 'Application No. 09', 'Application No. 09', 'Application No. 09', 'Application No. 09']

Patent US6098064 - Prefetching and caching documents according to probability ranked need S list - Google Patents
A method is presented for determining whether to prefetch and cache documents on a computer. In one embodiment, documents are prefetched and cached on a client computer from servers located on the Internet in accordance with their computed need probability. Those document with a higher need probability...http://www.google.com/patents/US6098064?utm_source=gb-gplus-sharePatent US6098064 - Prefetching and caching documents according to probability ranked need S list
Publication number US6098064 A
Application number US 09/083,645
Publication number 083645, 09083645, US 6098064 A, US 6098064A, US-A-6098064, US6098064 A, US6098064A
Inventors Peter L. Pirolli, James E. Pitkow
Patent Citations (4), Non-Patent Citations (22), Referenced by (451), Classifications (22), Legal Events (9)
US 6098064 A
1. A method for determining with a computer whether to prefetch and cache documents, comprising the steps of:
recording context data and history data of the documents in a needs list stored in a memory of the computer; said recording step being performed each time a document request is received by the computer;
computing a need probability for the documents recorded in the needs list stored in the memory; said computing step computing the need probability for the documents as a function of the recorded context data and history data of the documents; and
identifying those documents in the needs list with the greatest computed need probability to be prefetched and cached in the memory of the computer.
2. The method according to claim 1, wherein said step of recording history data further comprises the steps of:
recording in the needs list how recently each document is referenced; and
recording in the needs list how frequently each document is referenced.
3. The method according to claim 2, wherein said step of recording context data further comprises the steps of:
recording keywords of each document referenced in the needs list; and
recording links of each document referenced in the needs list.
4. The method according to claim 3, wherein said computing step further comprises the steps of:
estimating a history factor for predicting how likely each document recorded in the needs list is to be needed; and
estimating a context factor for predicting how relevant each document in the needs list is given a context Q of an operating environment.
6. The method according to claim 4, wherein said estimating step estimates the history factor according to the following equation: ##EQU4## where, ##EQU5## sets forth a predicted needs odds for a document per day; Di sets forth how many days since a document was last accessed;
Fi sets forth how frequently a document is accessed over a period of days; and
αβγ set forth parameters that are estimated from a population of documents.
fetching from a server documents in the needs list, beginning with those documents having the highest computed need probability; and
responsive to said fetching step, storing the fetched document in the memory of the computer.
identifying documents stored in the memory of the computer that are no longer necessary; and
relegating those identified documents to a server on a network to increase memory available for storing documents on the computer.
15. A method for determining with a computer whether to prefetch and cache documents, comprising the steps of:
recording frequency data and recency data of the documents in a needs list stored in a memory of the computer; said recording step recording in the needs list how recently the document is referenced and how frequently the document is referenced when a document request is received by the computer;
computing a need probability for the documents recorded in the needs list; said computing step computing the need probability for the documents as a function of the recorded frequency data and recency data; and
17. The method according to claim 15, wherein said computing step computes the need probability for each document in the needs list using the following equation: ##EQU6## where, ##EQU7## sets forth a predicted needs odds for a document per day; Di sets forth how many days since a document was last accessed;
18. An apparatus for determining whether to prefetch and cache documents, comprising:
a memory for storing a needs list of documents;
means for recording context data and history data of the documents in the needs list; said recording means recording the context data and the history data when a document request is received;
means for computing a need probability for the documents recorded in the needs list; said computing means computing the need probability for the documents as a function of the recorded context data and history data of the documents; and
means for identifying those documents in the needs list with the greatest computed need probability to be prefetched and cached in said memory.
19. The apparatus according to claim 18, wherein said recording means further comprises:
means for recording, in the needs list, how recently each document is referenced; and
means for recording, in the needs list, how frequently each document is referenced.
20. The apparatus according to claim 18, wherein said recording means further comprises:
means for recording, in the needs list, keywords of each document referenced; and
means for recording, in the needs list, links of each document referenced.
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U.S. Classification 1/1, 707/E17.12, 707/999.002, 707/999.005
Cooperative Classification Y10S707/99935, Y10S707/99932, H04L29/06, G06F17/30902, H04L69/329, H04L67/2852, H04L67/20, H04L67/28, H04L67/2847
European Classification G06F17/30W9C, H04L29/06, H04L29/08N19, H04L29/08N27, H04L29/08N27S4, H04L29/08N27S2
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