CN104699859A - Big data collection method based on knowledge engineering - Google Patents
Big data collection method based on knowledge engineering Download PDFInfo
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- CN104699859A CN104699859A CN201510163404.7A CN201510163404A CN104699859A CN 104699859 A CN104699859 A CN 104699859A CN 201510163404 A CN201510163404 A CN 201510163404A CN 104699859 A CN104699859 A CN 104699859A
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Abstract
The invention discloses a big data collection method based on knowledge engineering. The method comprises the steps of conducting classification on data in the knowledge engineering, collecting user information, search keywords input by a user or viewed content of the user, conducting correlation on the user information and department information, conducting matching on the search keywords or the viewed content and the classification of the knowledge engineering, conducting clustering on the classification corresponding to the search keywords or the viewed content, conducting statistics on classification data respectively according to a clustering result, conducting unified storage on the data and the user information to form a big database, and establishing correlation between the department information correlated to the user information and the big database. The big data collection method based on the knowledge engineering is suitable for requirements of the knowledge engineering.
Description
Technical field
The present invention relates to collecting method field, particularly, relate to a kind of cloud point extraction apparatus.
Background technology
Existing a lot of R&D enterprise, in its R&D process for many years, using or store accumulation has a lot of knowledge, and not only knowledge spreads all over each specialty, each field, and the form of knowledge is numerous, and due to research and development department many, knowledge distributing is in numerous operation systems.
In knowledge engineering, need store knowledge, existing knowledge store system, it has a lot of drawback.It lacks knowledge systematization, systematized management; Lack associating knowledge and business, be only piling up of simple knowledge, the needs of research staff's multi-control quick creation of knowledge can not be met, and service efficiency is low, low to the design effort contribution of research staff.In order to improve the utilization factor of data in knowledge engineering, adopt the mode of knowledge being carried out to intelligently pushing, by knowledge active push to research staff.To the propelling movement of knowledge based on large data principles, existing large collecting method is not suitable for the data acquisition of knowledge engineering.
Summary of the invention
Technical matters to be solved by this invention is to provide a kind of large collecting method of KBE.
The present invention's adopted technical scheme that solves the problem is:
The large collecting method of KBE, is characterized in that, comprising:
Data in knowledge engineering are classified;
The search key of collection user profile, user's input or browsing content;
User profile is associated with department information;
Search key or browsing content are mated with the classification of knowledge engineering;
To closing search key word or cluster is carried out in classification corresponding to browsing content;
Respectively grouped data is added up according to cluster result, data and user profile unification are stored, forms large database concept;
The department information of user information correlation is associated with large database concept.
In the method for the invention, knowledge data is classified, user profile is associated with described department information, and the search of the member of department, browsing information are gathered, form the large data of individual and department, be convenient to the pushing module of existing knowledge process according to the propelling movement of large data to relevant knowledge, while meeting department's development project demand, also meet the demand of individual to the preference of knowledge.
As preferably, when gathering the browsing content of user, the key word of browsing content is extracted.
To member, when namely the browsing content of user gathers, its data volume is large, directly extracts the key word of browsing content, is convenient to and the mating of classification.
As preferably, gathered the search key of user's input by webpage input.User retrieves content, and it is searched for by Webpage search hurdle, and the key word directly keyed in by search column can be gathered search key.
As preferably, described key word and the classification and matching of knowledge engineering adopt approximate match principle.
As preferably, in order to the demand further making the method meet knowledge process, make to push content and be associated with project business, the classification in described knowledge engineering is classified by item types.
To sum up, the invention has the beneficial effects as follows:
In the method for the invention, knowledge data is classified, user profile is associated with described department information, and the search of the member of department, browsing information are gathered, form the large data of individual and department, be convenient to the pushing module of existing knowledge process according to the propelling movement of large data to relevant knowledge, while meeting department's development project demand, also meet the demand of individual to the preference of knowledge.
Embodiment
Below in conjunction with embodiment, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.
Embodiment 1:
The large collecting method of KBE, is characterized in that, comprising:
Data in knowledge engineering are classified;
The search key of collection user profile, user's input or browsing content;
User profile is associated with department information;
Search key or browsing content are mated with the classification of knowledge engineering;
To closing search key word or cluster is carried out in classification corresponding to browsing content;
Respectively grouped data is added up according to cluster result, data and user profile unification are stored, forms large database concept;
The department information of user information correlation is associated with large database concept.
In the method for the invention, knowledge data is classified, user profile is associated with described department information, and the search of the member of department, browsing information are gathered, form the large data of individual and department, be convenient to the pushing module of existing knowledge process according to the propelling movement of large data to relevant knowledge, while meeting department's development project demand, also meet the demand of individual to the preference of knowledge.
Embodiment 2:
Extract for the ease of the direct key word to browsing content, be convenient to and mating of classifying, the present embodiment is optimized on the basis of above-described embodiment, namely when gathering the browsing content of user, extracts the key word of browsing content.
Embodiment 3:
The present embodiment has done refinement on the basis of above-described embodiment, is namely gathered the search key of user's input by webpage input.
Described key word and the classification and matching of knowledge engineering adopt approximate match principle.
Embodiment 4:
In order to the demand further making the method meet knowledge process, make to push content and be associated with project business, the present embodiment is optimized on the basis of above-described embodiment, and the classification in namely described knowledge engineering is classified by item types.
As mentioned above, the present invention can be realized preferably.
Claims (5)
1. the large collecting method of KBE, is characterized in that, comprising:
Data in knowledge engineering are classified;
The search key of collection user profile, user's input or browsing content;
User profile is associated with department information;
Search key or browsing content are mated with the classification of knowledge engineering;
To closing search key word or cluster is carried out in classification corresponding to browsing content;
Respectively grouped data is added up according to cluster result, data and user profile unification are stored, forms large database concept;
The department information of user information correlation is associated with large database concept.
2. the large collecting method of KBE according to claim 1, is characterized in that: when gathering the browsing content of user, extract the key word of browsing content.
3. the large collecting method of KBE according to claim 1, is characterized in that: the search key being gathered user's input by webpage input.
4. the large collecting method of KBE according to claim 1, is characterized in that: described key word and the classification and matching of knowledge engineering adopt approximate match principle.
5. the large collecting method of KBE according to claim 1, is characterized in that: the classification in described knowledge engineering is classified by item types.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201510163404.7A CN104699859A (en) | 2015-04-09 | 2015-04-09 | Big data collection method based on knowledge engineering |
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| CN201510163404.7A CN104699859A (en) | 2015-04-09 | 2015-04-09 | Big data collection method based on knowledge engineering |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN1963851A (en) * | 2006-12-06 | 2007-05-16 | 上海宝信软件股份有限公司 | System for managing knowledge facing cooperated work |
| CN101105795A (en) * | 2006-10-27 | 2008-01-16 | 北京搜神网络技术有限责任公司 | Network behavior based personalized recommendation method and system |
| WO2009084749A1 (en) * | 2007-12-28 | 2009-07-09 | Saltlux Inc. | Method for recommending contents with context awareness |
| CN103123641A (en) * | 2012-02-22 | 2013-05-29 | 深圳市谷古科技有限公司 | Social contact search method and device |
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2015
- 2015-04-09 CN CN201510163404.7A patent/CN104699859A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101105795A (en) * | 2006-10-27 | 2008-01-16 | 北京搜神网络技术有限责任公司 | Network behavior based personalized recommendation method and system |
| CN1963851A (en) * | 2006-12-06 | 2007-05-16 | 上海宝信软件股份有限公司 | System for managing knowledge facing cooperated work |
| WO2009084749A1 (en) * | 2007-12-28 | 2009-07-09 | Saltlux Inc. | Method for recommending contents with context awareness |
| CN103123641A (en) * | 2012-02-22 | 2013-05-29 | 深圳市谷古科技有限公司 | Social contact search method and device |
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Application publication date: 20150610 |
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