Methods, systems and techniques for providing search query suggestions based on non-personal data and user personal data according to availability of user personal data

1. A method, implemented on at least one computing device each of which has at least one processor, storage, and a communication platform connected to a network for query suggestion, the method comprising:

deriving a person corpus by cross-linking data from a public data source, a semi-private data source associated with a person and a private data source associated with the person, wherein the data is cross-linked based on cross-linking keys identified from the data;

extracting, from one or more data sources comprising the private data source and the semi-private data source, a plurality of queryable terms and attributes thereof;

normalizing the attributes by mapping, for each queryable term, the attributes onto one or more normalized features in a common feature space;

generating, for each queryable term, ranking values of the one or more normalized features, wherein a ranking value of each queryable term indicates one or more of: an importance of the queryable term with respect to the one or more data sources; a frequency or recentness of the queryable term appearing in content of the one or more data sources; and an importance of the content with respect to the one or more data sources, wherein the content includes the queryable term;

storing the plurality of queryable terms, the one or more normalized features associated with each queryable term, and the ranking values associated with each queryable term in the person corpus;

providing, to a personalized suggestion database, the plurality of queryable terms, the one or more normalized features associated with each queryable term, and the ranking values associated with each queryable term stored in the person corpus;

receiving a first portion of a query from the person;

receiving information indicative of an intent of the person;

obtaining, with respect to the first portion of the query, a first set of query suggestions from a non-personalized suggestion database, wherein the non-personalized suggestion database is based on information from a first data source generated independently of the person corpus;

receiving, subsequent to the first portion of the query, a second portion of the query from the person;

modifying, based on the intent of the person, a combination of the first and second portions of the query to generate a modified query;

obtaining, with respect to both of the received query and the modified query, a second set of query suggestions obtained from the personalized suggestion database;

ranking query suggestions in the first and second sets based on a usage of an application of the one or more data sources, wherein a query suggestion is ranked higher if a first frequency that the person accesses the application exceeds a threshold within a period of time and the first frequency is higher than a second frequency that the person accesses a second application of the one or more data sources; and

presenting the ranked query suggestions to the person to facilitate the person to complete the query.

2. The method of claim 1 , wherein the first data source includes:

a person search history; and

an archive of regular suggestions.

3. The method of claim 1 , wherein the private data source includes one or more of:

private electronic mails;

a private calendar;

a private contact list;

private messages;

private bookmarks;

private visual information;

private voice information; and

private log information.

4. A system having at least one processor, storage, and a communication platform, to provide query suggestions, the system comprising:

a person corpus construction engine implemented by at least one processor and configured to:

derive a person corpus by cross-linking data from a public data source, a semi-private data source associated with a person and a private data source associated with the person, wherein the data is cross-linked based on cross-linking keys identified from the data,

extract, from one or more data sources comprising the private data source and the semi-private data source, a plurality of queryable terms and attributes thereof,

normalize the attributes by mapping, for each queryable term, the attributes onto one or more normalized features in a common feature space,

generate, for each queryable term, ranking values of the one or more normalized features, wherein a ranking value of each queryable term indicates one or more of: an importance of the queryable term with respect to the one or more data sources; a frequency or recentness of the queryable term appearing in content of the one or more data sources; and an importance of the content with respect to the one or more data sources, wherein the content includes the queryable term,

store the plurality of queryable terms, the one or more normalized features associated with each queryable term, and the ranking values associated with each queryable term in the person corpus, and

provide, to a personalized suggestion database, the plurality of queryable terms, the one or more normalized features associated with each queryable term, and the ranking values associated with each queryable term stored in the person corpus;

a request processing unit implemented using the at least one processor and configured to

receive a first portion of a query from the person,

receive information indicative of an intent of the person, and

receive, subsequent to the first portion of the query, a second portion of the query from the person;

a first suggestion retrieving module implemented using the at least one processor and configured to

obtain, with respect to the first portion of the query, a first set of query suggestions from a non-personalized suggestion database, wherein the non-personalized suggestion database is based on information from a first data source generated independently of the person corpus,

modify, based on the intent of the person, a combination of the first and second portions of the query to generate a modified query, and

obtain, with respect to both of the received query and the modified query, a second set of query suggestions obtained from the personalized suggestion database;

a suggestion ranking module implemented using the at least one processor and configured to rank query suggestions in the first and second sets based on a usage of an application of the one or more data sources, wherein a query suggestion is ranked higher if a first frequency that the person accesses the application exceeds a threshold within a period of time and the first frequency is higher than a second frequency that the person accesses a second application of the one or more data sources; and

a query suggestion generation module implemented using the at least one processor and configured to present the first set and second set of query suggestions to the person to facilitate the person to complete the query.

5. The system of claim 4 , wherein the first data source includes:

a person search history; and

an archive of regular suggestions.

6. The system of claim 4 , wherein the private data source includes one or more of:

private electronic mails;

a private calendar;

a private contact list;

private messages;

private bookmarks;

private visual information;

private voice information; and

private log information.

7. A non-transitory machine-readable medium having information recorded thereon to provide query suggestions, wherein the information, when read by the machine, causes the machine to perform operations comprising:

deriving a person corpus by cross-linking data from a public data source, a semi-private data source associated with a person and a private data source associated with the person, wherein the data is cross-linked based on cross-linking keys identified from the data;

extracting, from one or more data sources comprising the private data source and the semi-private data source, a plurality of queryable terms and attributes thereof;

normalizing the attributes by mapping, for each queryable term, the attributes onto one or more normalized features in a common feature space;

generating, for each queryable term, ranking values of the one or more normalized features, wherein a ranking value of each queryable term indicates one or more of: an importance of the queryable term with respect to the one or more data sources; a frequency or recentness of the queryable term appearing in content of the one or more data sources; and an importance of the content with respect to the one or more data sources, wherein the content includes the queryable term;

storing the plurality of queryable terms, the one or more normalized features associated with each queryable term, and the ranking values associated with each queryable term in the person corpus;

providing, to a personalized suggestion database, the plurality of queryable terms, the one or more normalized features associated with each queryable term, and the ranking values associated with each queryable term stored in the person corpus;

receiving a first portion of a query from the person;

receiving information indicative of an intent of the person;

obtaining, with respect to the first portion of the query, a first set of query suggestions from a non-personalized suggestion database, wherein the non-personalized suggestion database is based on information from a first data source generated independently of the person corpus;

receiving, subsequent to the first portion of the query, a second portion of the query from the person;

modifying, based on the intent of the person, a combination of the first and second portions of the query to generate a modified query;

obtaining, with respect to the received query and the modified query, a second set of query suggestions obtained from the personalized suggestion database;

ranking query suggestions in the first and second sets based on a usage of an application of the one or more data sources, wherein a query suggestion is ranked higher if a first frequency that the person accesses the application exceeds a threshold within a period of time and the first frequency is higher than a second frequency that the person accesses a second application of the one or more data sources; and

presenting the ranked query suggestions to the person to facilitate the person to complete the query.

8. The medium of claim 7 , wherein the first data source includes:

a person search history; and

an archive of regular suggestions.

9. The medium of claim 7 , wherein the private data source includes one or more of:

private electronic mails;

a private calendar;

a private contact list;

private messages;

private bookmarks;

private visual information;

private voice information; and

private log information.

10. The method of claim 1 , wherein the first portion of the query corresponds to a prefix of a search query.

11. The method of claim 1 , wherein the second set of query suggestions is presented replacing the presentations of the first set of query suggestions.

12. The method of claim 1 , wherein the modified portion of the query is generated by modifying a concatenation of the first portion of the query and the second portion of the query, and wherein at least a portion of the modified portion of the query is generated independently of previous queries.

13. The system of claim 4 , wherein the modified portion of the query is generated by modifying a concatenation of the first portion and the second portion of the query, and wherein at least a portion of the modified portion of the query is generated independently of previous queries.

14. The medium of claim 7 , wherein the modified portion of the query is generated by modifying a concatenation of the first portion and the second portion of the query, and wherein at least a portion of the modified portion of the query is generated independently of previous queries.

15. The method of claim 1 , wherein the importance of the content with respect to the one or more data sources is based on importance of an email including the queryable term.

16. The method of claim 1 , further comprising:

determining a domain of the data; and

identifying the cross-linking keys from the data based on the domain.

17. The method of claim 1 , further comprising:

estimating the intent of the person based on tracking interactions of the person with the person corpus.

18. The method of claim 1 , wherein the ranking is further based on a location and a time of the person.

19. The method of claim 1 , further comprising:

generating, based on the intent of the person and information included in the person corpus, a card for answering the query.

20. The method of claim 1 , wherein the second set of query suggestions comprise one or more personalized query suggestions, and

wherein the step of obtaining the second set of query suggestions comprises: obtaining the one or more personalized query suggestions from a personalized cache.