Identification of semantic units from within a search query

Claim 3

The method of claim 1 , wherein the selection of the semantic units further includes: selecting semantic units from the generated substrings that have calculated values above a predetermined threshold.

Claim 4

The method of claim 1 , wherein the calculated values are weighted based on a ranking defined by relevance of the identified documents, such that substrings that occur in more relevant ones of the identified documents are assigned higher calculated values than substrings that occur in less relevant ones of the documents.

Claim 5

The method of claim 1 , wherein the calculated values are weighted based on a ranking defined by relevance of the identified documents, such that an occurrence of a substring in a more relevant one of the identified documents is weighted more than an occurrence of the substring in a less relevant one of the documents.

Claim 10

The method of claim 6 , wherein the identified subset includes a predetermined number of the most relevant ones of the documents in the list of relevant documents.

Claim 11

The method of claim 6 , wherein the calculated values are weighted based on a ranking defined by relevance of the identified documents, such that substrings that occur in more relevant ones of the documents are assigned higher calculated values than substrings that occur in less relevant ones of the documents.

Claim 12

The method of claim 6 , wherein the calculated values are weighted based on a ranking defined by relevance of the identified documents, such that an occurrence of a substring in a more relevant one of the identified documents is weighted more than an occurrence of the substring in a less relevant one of the documents.

Claim 13

A computer-readable medium storing instructions for causing at least one processor to perform a method that identifies semantic units within a search query, the method comprising: identifying documents relating to the query by matching individual search terms in the query to an index of a corpus, the identification of the documents further including generating an initial list of relevant documents and selecting a predetermined number of the most relevant documents in the initial list to include in the identified documents; forming a plurality of multiword substrings of the query in which each of the substrings includes at least two words; calculating, for each of the substrings, a value relating to the portion of the identified documents that contain the substring; selecting semantic units from the generated multiword substrings based on the calculated values; and storing the selected semantic units in a memory.

Claim 14

A computer-readable medium storing instructions for causing at least one processor to perform a method that identifies semantic units within a search query, the method comprising: identifying documents relating to the query by matching individual search terms in the query to an index of a corpus, the identification of the documents further including generating an initial list of relevant documents and selecting a predetermined number of the most relevant documents in the initial list to include in the identified documents; forming a plurality of multiword substrings of the query in which each of the substrings includes at least two words; calculating, for each of the substrings, a value relating to the portion of the identified documents that contain the substring; selecting semantic units from the generated multiword substrings based on the calculated values; and storing the selected semantic units in a memory.

Claim 15

A computer-readable medium storing instructions for causing at least one processor to perform a method that identifies semantic units within a search query the method comprising: identifying documents relating to the query by matching individual search terms in the query to an index of a corpus; forming a plurality of multiword substrings of the query in which each of the substrings includes at least two words; calculating for each of the substrings a value relating to the portion of the identified documents that contain the substring; selecting semantic units from the generated multiword substrings based on the calculated values; and storing the selected semantic units in a memory, wherein the selection of the semantic units further includes selecting semantic units from the generated substrings that have calculated values above a predetermined threshold and discarding substrings that overlap other substrings with a higher calculated value.

Claim 16

A computer-readable medium storing instructions for causing at least one processor to perform a method that identifies semantic units within a search query the method comprising: identifying documents relating to the query by matching individual search terms in the query to an index of a corpus; forming a plurality of multiword substrings of the query in which each of the substrings includes at least two words; calculating for each of the substrings a value relating to the portion of the identified documents that contain the substring; selecting semantic units from the generated multiword substrings based on the calculated values; and storing the selected semantic units in a memory, wherein the selection of the semantic units further includes selecting semantic units from the generated substrings that have calculated values above a predetermined threshold and discarding substrings that overlap other substrings with a higher calculated value.

Claim 17

The computer-readable medium of claim 11 , wherein the calculated values are weighted based on a ranking defined by relevance of the identified documents, such that substrings that occur in more relevant documents are assigned higher calculated values than substrings that occur in less relevant documents.

Claim 18

The computer-readable medium of claim 11 , wherein the calculated values are weighted based on a ranking defined by relevance of the identified documents, such that an occurrence of a substring in a more relevant one of the identified documents is weighted more than an occurrence of the substring in a less relevant one of the documents.

Claim 19

A computer-readable medium storing instructions for causing a processor to perform a method, the method comprising: receiving a search query from a user; generating a list of relevant documents based on individual search terms of the query; identifying a subset of documents that are the most relevant documents from the list of relevant documents; forming a plurality of multiword substrings of the query in which each of the multiword substrings includes at least two words; calculating, for each of the substrings, a value related to the portion of the subset of documents that contain the substring; selecting semantic units from the generated multiword substrings based on the calculated values; refining the generated list of relevant documents based on the selected semantic units; and transmitting the refined list of relevant documents to the user, wherein the selection of the semantic units further includes selecting semantic units from the generated substrings that have calculated values above a predetermined threshold and discarding substrings that overlap other substrings with a higher calculated value.

Claim 20

A computer-readable medium storing instructions for causing a processor to perform a method, the method comprising: receiving a search query from a user; generating a list of relevant documents based on individual search terms of the query; identifying a subset of documents that are the most relevant documents from the list of relevant documents; forming a plurality of multiword substrings of the query in which each of the multiword substrings includes at least two words; calculating, for each of the substrings, a value related to the portion of the subset of documents that contain the substring; selecting semantic units from the generated multiword substrings based on the calculated values; refining the generated list of relevant documents based on the selected semantic units; and transmitting the refined list of relevant documents to the user, wherein the selection of the semantic units further includes selecting semantic units from the generated substrings that have calculated values above a predetermined threshold and discarding substrings that overlap other substrings with a higher calculated value.

Claim 21

The computer-readable medium of claim 14 , wherein the identified subset includes a predetermined number of the most relevant documents from the list of relevant documents.

Claim 22

The computer-readable medium of claim 14 , wherein the calculated values are weighted based on a ranking defined by relevance of the identified documents, such that substrings that occur in more relevant documents are assigned higher calculated values than substrings that occur in less relevant documents.

Claim 23

The computer-readable medium of claim 14 , wherein the computer-readable medium is a CD-ROM, floppy disk, tape, flash memory, system memory, hard drive, or data signal embodied in a carrier wave.

Claim 24

The computer-readable medium of claim 14 , wherein the calculated values are weighted based on a ranking defined by relevance of the identified documents, such that an occurrence of a substring in a more relevant one of the identified documents is weighted more than an occurrence of the substring in a less relevant one of the documents.

Claim 27

The system of claim 19 , wherein the processor refines the identified list of documents based on the selected semantic units.

Claim 28

The system of claim 20 , wherein the system transmits the refined list of documents to the user.

Claim 29

The system of claim 19 , wherein the network is the Internet and the corpus is a collection of web documents.

Claim 30

The system of claim 19 , wherein the calculated values are weighted based on a ranking defined by relevance of the identified documents, such that substrings that occur in more relevant documents are assigned higher calculated values than substrings that occur in less relevant documents.

Claim 31

The system of claim 19 , wherein the calculated values are weighted based on a ranking defined by relevance of the identified documents, such that an occurrence of a substring in a more relevant one of the identified documents is weighted more than an occurrence of the substring in a less relevant one of the documents.

Claim 32

A server comprising: a processor; and a memory operatively coupled to the processor, the memory including: a ranking component configured to return a list of documents ordered by relevance in response to a search query; and a semantic unit locator component configured to locate semantic units, each having a plurality of words, in search queries entered by a user based on a predetermined number of most relevant documents in the list of documents returned by the ranking component, the located semantic units being stored in the memory, wherein the semantic unit locator is further configured to generate a plurality of substrings of the query, calculate, for each generated substring, a value relating to the portion of the predetermined number of the most relevant documents that contain the substring, and locate the semantic units from the generated values.

Claim 33

A server comprising: a processor; and a memory operatively coupled to the processor, the memory including: a ranking component configured to return a list of documents ordered by relevance in response to a search query; and a semantic unit locator component configured to locate semantic units, each having a plurality of words, in search queries entered by a user based on a predetermined number of most relevant documents in the list of documents returned by the ranking component, the located semantic units being stored in the memory, wherein the semantic unit locator is further configured to generate a plurality of substrings of the query, calculate, for each generated substring, a value relating to the portion of the predetermined number of the most relevant documents that contain the substring, and locate the semantic units from the generated values.

Claim 34

The server of claim 25 , further including: a search engine configured to refine the list of documents based on the located semantic units.

Claim 35

The server of claim 26 , wherein the processor is configured to: transmit the refined list of documents to a user that provided the query.

Claim 36

The server of claim 25 , wherein the semantic unit locator is configured to locate semantic units from the generated substrings that have calculated values above a predetermined threshold.

Claim 37

The server of claim 28 , wherein the semantic unit locator is configured to discard substrings that overlap other substrings with a higher calculated value.

Claim 38

The server of claim 25 , wherein the calculated values are weighted based on a ranking defined by relevance of the identified documents, such that substrings that occur in more relevant documents are assigned higher calculated values than substrings that occur in less relevant documents.