Source: http://www.google.com.hk/patents/US8086594?hl=zh-TW
Timestamp: 2013-05-24 11:57:15
Document Index: 150899223

Matched Legal Cases: ['Application No. 2005203237', 'Application No. 2005203238', 'Application No. 2005203239', 'Application No. 2005203240', 'Application No. 200510085370', 'Application No. 200510085371', 'Application No. 200510085372', 'Application No. 200510085373']

�M�Q US8086594 - Bifurcated document relevance scoring - Google �M�Q�j�M �Ϥ� �a�� Play YouTube �s�D Gmail ���ݵw�� ��h »�i���M�Q�j�M | �������� | �n�J�i���M�Q�j�M�M�QAn information retrieval system uses phrases to index, retrieve, organize and describe documents. Phrases are extracted from the document collection. Documents are the indexed according to their included phrases, using phrase posting lists. The phrase posting lists are stored in an cluster of index servers....http://www.google.com.hk/patents/US8086594?utm_source=gb-gplus-share�M�Q US8086594 - Bifurcated document relevance scoring���}��US8086594 B1�X���������v�ӽЮѽs��11/694,797�o�G���2011�~12��27���ӽФ��2007�~3��30�� �u���v���2007�~3��30���o��HPei CaoSoham MazumdarVaibhav MehtaYonatan Zunger��M�Q�v�HGoogle Inc. ���M�Q������707/713��ڱM�Q������G60F17/30�ѦҤ��m�M�Q�ޥ� (102)�D�M�Q�ޥ� (78)�Q�H�U�M�Q�ޥ� (2)�~���s�����M�Q�ӼЧ� ���M�Q�ӼЧ��M�Q����T�� �ڬw�M�Q��Bifurcated document relevance scoringUS 8086594 B1�K�n An information retrieval system uses phrases to index, retrieve, organize and describe documents. Phrases are extracted from the document collection. Documents are the indexed according to their included phrases, using phrase posting lists. The phrase posting lists are stored in an cluster of index servers. The phrase posting lists can be tiered into groups, and sharded into partitions. Phrases in a query are identified based on possible phrasifications. A query schedule based on the phrases is created from the phrases, and then optimized to reduce query processing and communication costs. The execution of the query schedule is managed to further reduce or eliminate query processing operations at various ones of the index servers.
The quick brown ��The quick brown fox
fox jumps over ��fox jumps over the
jumps over the ��jumps over the lazy
��.�� indicates body, final, 4
��The quick brown fox jumps�� 1 initial point
��fox jumps over the lazy�� 1 medial point
��jumps over the lazy god�� 1 final point
��brown fox jumps over�� 1 medial point
In this first embodiment, each of the P phrase posting lists is partitioned into a number (5) of portions called ��shards��; the partitioning process can be called ��sharding.�� Each posting list shard will ultimately be stored by one (or more) of the index servers 160. For purposes of explanation, during indexing a posting list shard will be called a segment shard because it will be stored to the segment shard files 225; once an indexing pass is completed, the segment shard files are copied over to the index shard files 165 and form corresponding index shards (and thus the current index), and then copied to the index servers 200 for serving. An index shard may be stored by an index server 200 in memory, on disc, in a combination thereof. Thus, in FIG. 4, there is shown index server 200.1 through 200.S; for example, if S=1000, then there will be 1000 shards of each phrase posting list. Index server 200.1 stores the first shard, shard 1, for each of the phrase posting list, lists 1 through P; index server 200.2 stores shard 2 for all of the phrase posting lists, and so forth through index server 200.S, which stores the Sth shard for all phrase posting lists. For clarity, it should be noted that an index server 200 operates as server program in a computer, and a given computer can support multiple index servers 200; thus a given server computer can store the phrase posting lists for multiple shards (i.e., shards Si for some set of values of i<=S). Additionally, a given shard (e.g. one containing high frequency phrases) may be duplicated and stored on multiple index servers 200 in order to increase performance.
��New�� AND ��York Ethiopian�� AND�� restaurants��
��New York�� AND ��Ethiopian�� AND�� restaurants��
ƒ(N)=(�]N /N 1+�\), where �\=an adjustable constant such that �\>0 to adjust precision of phrase phrasification (higher a increases the precision and reduces the recall), and �]=an adjustable constant such that 0<�]<1 to adjust the bias against obtaining too many phrases (smaller �] reduces the recall) The �\ and �] parameters are adjusted by the system designer to trade off the precision and recall of the resulting search for the phrase phrasification.
minimum[cost(Yi)]��minimum[cost(Xij)], or if
minimum[cost(Yi)]��maximum[cost(Xij)].
minimum[cost(Yi)]��
��new york restaurant�� ��new york�� AND ��restaurant��
��new york restaurants�� ��new york�� AND ��restaurants��
The above process by which the query schedule is passed from one index server to another can be further improved as follows: An explicit data node can only present in a query schedule if its parent is an AND node. This AND node will be scheduled at the same set of servers as some other child thereof, and the explicit data node (i.e., document list) will be intersected with this child. If this child is distributed across multiple index servers�Xi.e., if the phrase posting list corresponding to that child phrase is divided into multiple shards�Xit is only necessary to forward to each index server that portion of the document list which has the potential of forming a non-empty intersection with the shard(s) served by the recipient index server. A requesting server can determine which documents need to be transmitted to which recipient server by using the document number of each document and the shard assignment function; this will identify which of its documents could be at the recipient server. For example, consider the query (A AND B), where phrase A is found in a tier containing S1 shards, and phrase B is found in a tier containing S2>S1 shards. Then a document in shard m of A, where 0��m��S1, is guaranteed to never intersect a document in shard n of B, where 0��n��S2, unless n=m (modulo S1). This immediately reduces the number of communications needed between servers containing shards of A and servers containing shards of B by a factor of S2/S1.
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