CN109783067A - Intelligent knowledge integration and searching system and method based on ontology CallCenter platform - Google Patents
Intelligent knowledge integration and searching system and method based on ontology CallCenter platform Download PDFInfo
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Abstract
The invention belongs to technical field of software development, specially the intelligent knowledge integration and searching system and method for the Call Center O&M service platform based on ontology.System includes: document processor, inquires conversion module, acts on behalf of retrieval module, customized treatment module, user interface and ontology library and information bank；User passes through user interface input inquiry sentence；Inquiry conversion module searches corresponding concept into ontology library, according to concept matched in domain body, carries out inquiry conversion to this inquiry according to gained information, is then inquired by retrieval agent module into information bank；The customized processing module processing of resulting result is inquired, query result is shown by user interface.The present invention provides the user with more humanized service；O&M is allowed to adapt to the demand of user；It realizes accurate integration matching retrieval, allows the information of knowledge base that trend is followed to make rapid progress.
Description
Technical field
The invention belongs to technical field of software development, and in particular to a kind of Call Center O&M service based on ontology
Intelligent knowledge integration and searching system and the method for platform.
Background technique
IT service management (ITSM) it be a set of high quality method, help tissue effectively manage, develop, implement and grasp
Make system.As Process-Oriented and method customer-centric, ITSM is improved in tissue by integrated service and business
Service and service support.Compared with international standard, other than needing management perfection system, operation flow and institutional framework, the portion
Door also needs an electronic maintaining-managing system, powerful operational administrative system, carries out operation flow, personnel arrangement pipe
Reason, improves the efficiency of service and quality of department.
Realize that information management will be helpful to realize IT service goal in service management.In recent years, opening in ITSM project
In hair and application, the foundation and management of knowledge base are knowledge accumulation, propagation and shared indispensable module, improve operation
Speed and quality.The information management of ITSM, can handle event and problem, extend efficient help, and encounter in the daily work
Information investigation, Operation and maintenance service station, the relevant information of two, three line support staff's routine works can be submitted to knowledge
In library.In this way, the conversion from recessive experience to Explicit Knowledge is formed, and is finally completed accumulation of knowledge.
The core of information management is knowledge Modeling.And the key of knowledge Modeling is how effectively to express knowledge, that is, is known
Knowing indicates.Common knowledge representation method includes: that predicate logic indicates, frame indicates, production rule indicates, script, semantic network
It indicates, object-oriented representation and ontology.Predicate logic expression, frame expression, production rule expression, script, semantic network indicate and
Object-oriented representation has different degrees of deficiency, therefore is difficult to directly apply to the knowledge table in ITSM operation and maintenance field
Show.
Ontological concept originates from philosophy field, is the clear formal specification of shared conceptual model.The core of ontology definition
The heart is the essence that things is understood based on the explicit definition of abstract type and its relation constraint, to realize to complicated cognitive knowledge
Specification description.Ontology has accurately expression, standard and clearly structure feature in field of knowledge representation, is conducive to knowledge
It reuses and shared.In recent years, Ontological concept is introduced knowledge engineering by researcher, is realized knowledge sharing, interoperability, can be safeguarded
Property, the functions such as reusability, be widely used in the neck such as knowledge engineering, information technology, artificial intelligence, engineering in medicine, mechanical engineering
Domain.IT system itself involved in knowledge itself, inherently without structure, uncertainty and empiricism.Therefore, how scientific
Ground manages these knowledge, in conjunction with the problems in ITIL management and incident management, the existing operation of tissue and maintenance is made full use of to know
Know resource, improves operation management level and maintenance knowledge is very important.
As described above, a kind of Domain Modeling method of the ontology as development, is widely used in knowledge engineering, semantic net
Equal fields.This is because ontology have the characteristics that it is following prominent:
(1) interoperability and succession between not homologous ray may be implemented in ontology, and method is in different modeling methods, example, language
It makes peace and is converted between software tool and mapped.The characteristics of just meeting O&M knowledge connection；
(2) ontology realizes the representation of knowledge using extending mark language technology, and expressed knowledge is made to can satisfy operation and maintenance
The feature of knowledge, scalability and opening has good concept hierarchy；
(3) for Knowledge Management System, ontology is exactly a vocabulary.Ontology can more accurately define object knowledge
Concept and relationship each other.Such as synonym, upper hyponym etc..Realize semantic-based retrieval；
Under the support of this series of concepts, knowledge search, knowledge accumulation and Efficiency of Knowledge Sharing will be greatly improved, and really be known
Weight sensing will also be become a reality with knowledge sharing.This has also just corresponded to the probabilistic spy of the knowledge such as the solution being related to
Sign.
(4) by the various information progress to tissue, clearly semantic description, ontology can be by unstructured and half structures
Change information and is converted into structured storage knowledge.Most of all, ontology provides a rigorous and abundant theoretical field, and
The structure of not only one storing data.
Indicate that standard and exchange agreement establish knowledge base using ontology modeling method and relevant knowledge, convenient between researcher
Exchange, collaborative development, cross-platform method between different field, different model, number can be achieved for computer system
According to, the conversion of task, tool and shared.
Meanwhile ontology being introduced into the knowledge Modeling of knowledge base, establish domain ontology repository.Knowledge is to pass through art
Language or concept disclose the inner link between knowledge come what is expressed.In domain ontology repository, the tissue of knowledge is not only
Longitudinal scope further includes semantic association, ontology association.Inference machine is made inferences using this knowledge, which greatly improves
The memory and accuracy of user's search.
Traditional service platform disadvantage is very obvious:
1, traditional O&M service platform impersonality, not instead of the offer service of customer-centric, allow user adaptation
The specification that O&M department formulates；
2, the question and answer to customer problem are manually carried out, not only service quality cannot ensure and need to carry out phase to service personnel
The training of knowledge is closed, thus uncertain and O&M cost becomes more；
3, manpower and physical resource waste are serious.With information-based fast development, and the IT system scale of each each individual region
All be not quite similar, be just initially may number of users it is seldom, IT system is small, but with the development of unit and it is information-based into
The acceleration of journey, number of users rapid growth, IT system scale is more and more huger, and IT resource is more and more.Blindness can only be passed through
It updates hardware resource and increases the investment of manpower to adapt to the demand of IT O&M, lead to the significant wastage of human and material resources.
Summary of the invention
It is an object of the invention to propose a kind of simple, efficient, practical Call Center O&M service based on ontology
Intelligent knowledge integration and searching system and the method for platform to offer convenience in the routine work of operation maintenance personnel, while being also use
Efficient O&M is brought to experience in family.
The characteristics of present invention is designed according to the whole IT Service management process of Call Center O&M service platform is constituted
And element, firstly, proposing the Knowledge Representation Model frame based on ontology；Then, by Knowledge Representation Model frame and knowledge base
Phase mapping is constructed, realizes the Knowledge Representation Model storage of Call Center O&M service platform；Finally, to the tool based on ontology
There are key technology in the knowledge retrieval frame of semantic feature and the semantic algorithm being related to be studied；It develops and realizes a base
In the intelligent knowledge integration and search method and system of the Call Center O&M service platform of ontology.It is big that the present invention is divided into two
Part: a part is the pretreatment of ontology data, and a part is the retrieval of O&M information.The pretreatment of ontology data, including it is logical
It crosses data source and gets data, pass data to document processor；Data source is given every in O&M and user information database
A information point carries out the lexical analysis of text, and the result after analysis is stored into field ontology library and information bank, building fortune
Dimension data ontology；Then, the retrieval of O&M information is carried out, comprising: extract in text from non-structured text information
Useful information, and the mapping relations between the vocabulary of text and concept are established in the concept in document processor according to field, it will
These non-structured O&M information and the foundation of the domain body of structuring contact, and are assisted using the knowledge of the structuring of ontology
Retrieve non-structured text information.
Intelligent knowledge integration provided by the invention and searching system, it is shown in Figure 1 comprising: document processor, inquiry
Conversion module acts on behalf of retrieval module, customized treatment module, user interface and ontology library and information bank；Wherein:
The user interface, user pass through interface input inquiry sentence；And show query result；
The document processor, for handling the data transmitted from data source, including, O&M and use are given to data source
Text conversion in document is word, logarithm firstly, carrying out the lexical analysis of text by each information point in the information bank of family
Word, hyphen, punctuate and letter capital and small letter handled；Then, removed in O&M and user information using disabling vocabulary
Function word filters out those and acts on little word for retrieval, is only named the word or phrase that word, verb etc. are of practical significance；So
Afterwards, stem extraction is carried out to obtained phrase, removes front and back and sews, so that the grammer variation word of query term can also be retrieved；It connects
, index entry is selected, determines which word or stem, phrase are used as index element, obtains the concept that can correctly express literature content
Property word or phrase；The mapping relations between the vocabulary of text and concept are established according to the concept in field；These are non-structured
O&M information and the foundation of the domain body of structuring contact, and assist to retrieve using the knowledge of the structuring of ontology non-structured
Text information.Finally, storing analysis result into field ontology library and information bank；
The above results are searched corresponding concept by the inquiry conversion module, block into ontology library, carry out language to obtained concept
Adoptedization processing；And according to concept matched in domain body, inquiry conversion is carried out to this inquiry according to gained information, according to
The user query sentence that family interface is transmitted carries out inquiry conversion to this inquiry according to information, as query semantics judgement and look into
Extension is ask, makes inquiry that there is corresponding semantic information；And retrieval agent module is given these information；
It is described to act on behalf of retrieval module, it according to the information that transmits of inquiry conversion module, is inquired into information bank, to not can determine that
The inquiry of semantic information is inquired according to keyword match technique；It inquires resulting result and passes to customized treatment resume module；
The customized treatment module, according to term original word query result, term synonym query result, term hypernym
Query result, term hyponym query result are ranked up, and user interface is then transferred to show query result；
The ontology library, for storing the O&M Information Ontology of building, O&M Information Ontology includes the correlation of Domain-specific ontology
Knowledge also includes the information of the various services provided, such as type parameter and its relevant operation class；
Described information storehouse, as ontology library, for storing the O&M Information Ontology of building.
The query statement that user is inputted by user interface obtains the conceptual word or word that can correctly express inquiry sentence semanteme
Result is passed to inquiry conversion module by group；The above results are searched corresponding concept by inquiry conversion module into ontology library, right
Obtained concept carries out semantization processing；And according to concept matched in domain body, conversion module is inquired according to gained information
Inquiry conversion is carried out to this inquiry, such as the judgement and query expansion of query semantics, makes inquiry that there is corresponding semantic information, so
After give retrieval agent module and inquired into information bank, to not can determine that the inquiry of semantic information according to Keywords matching skill
Art is inquired；The customized processing module processing of resulting result is inquired, it is synonymous according to term original word query result, term
Word query result, term hypernym query result, term hyponym query result are ranked up, and are then shown by user interface
Show query result.
The present invention is directed to the target of information retrieval under Call Center O&M service environment, gives full play to Call Center
O&M services the automatic ability of itself, reinforces the use to UDDI registration information and LDAP information, is giving full play to grid
Ontology is constructed on the basis of ability, here it is the building of O&M Information Ontology proposed by the present invention theories.
The building O&M Information Ontology, including data are got from data source, pass data to document processor；Text
Shelves processor gives each information point in O&M and user information database to data source, firstly, carrying out the lexical analysis of text, i.e.,
It is word by the text conversion in document, the capital and small letter of number, hyphen, punctuate and letter is handled, then utilizes disabling
Vocabulary removes the function word in O&M and user information, filters out those and acts on little word for retrieval, is only named word, verb
Etc. the word or phrase being of practical significance；Then stem extraction is carried out to obtained phrase, removes front and back and sew, so that the language of query term
Method variation word can also be retrieved；Then index entry is selected, determines which word or stem, phrase are used as index element, obtains energy
The conceptual word or phrase of correct expression literature content；Finally analysis result is stored into field ontology library and information bank.So
The useful information in text is extracted from non-structured text information by information retrieval afterwards, and is built according to the concept in field
Mapping relations between the vocabulary and concept of vertical text.
In the building process of O&M Information Ontology, on the basis of combining O&M self-ability, there is following building rule:
(1) Call Center O&M service system ability is given full play to
The various information that O&M itself provides and service provide possibility for the building of O&M ontology.Intention gives full play to fortune
The structuring capacity for tieing up itself, comprising constructing O&M ontology using UDDI registration information and LDAP information；
(2) sufficiently multiplexing
Herein after establishing domain body, O&M Information Ontology is constructed using domain body, gives full play to O&M domain body
Multiplexing capacity；
(3) body size appropriateness
For O&M ontology on the basis of giving full expression to semantic information, the concept number for including in ontology should be minimum as far as possible
Change, as far as possible by redundancy removal.
The thought proposed by the present invention that ontology is constructed under O&M environment can effectively be alleviated to establish by domain expert and transport
Tie up the difficulty of ontology.
About LDAP(Light Directory Access Protocol), it is dynamic that the present invention monitors resource using LDAP Directory Service Technology
State, essence are exactly the various resources with object technology and hierarchical fashion display system, and then monitoring information is stored to platform
In information bank, so that user uses at any time, while the uniform logical view an of gridding resource is provided for user.LDAP clothes
Be engaged in device in logic use centralized management and access control, support resource information distribution store and backup, for access net
The resource information of flood tide, dynamic and isomery under lattice ring border provides unified access mechanism.LDAP dynamic is agile easily to be extended
Feature facilitates the inquiry of user, the lightweight protocol of browsing and search；For with inquiry conversion module, retrieval agent module
Data query and communication between ontology library information bank.
Call Center O&M service ontology of the present invention, according to the characteristics of Call Center and ability and this
Combinations matches in the environment of body building produce some new characteristics:
(1) conversion of the describing mode of user's request.In order to realize the matching of ontology and ontology, it would be desirable to the description of user
It is converted into ontology describing；
(2) pretreatment of ontology.Before carrying out the figure matching of grid ontology, need the description grid field in grid ontology
The OWL file of ontology or the OWL-S file for describing Grid Services Based on Ontology are converted to figure shape or tree, for figure
Premise preparation is carried out in the input matched；
(3) classification and matching of ontology.The grid ontology constructed in the case where grid building is theoretical is divided into grid domain body and net
Lattice service ontology, describing mode and memory space difference, the complexity for the requirement that in addition grid user search condition is transformed
Property is also different.So the matching of grid ontology is divided into the matching of grid domain body and of Grid Services Based on Ontology herein
With two aspects；
(4) when ontological construction, no matter grid domain body or Grid Services Based on Ontology are all using tree construction as storage mode, and this
The storage organization of body is undoubtedly suitable for the figure matching technique of ontology；
(5) in existing Ontology Matching, due to going deep into for Call Center service idea, all in grid are all abstracted into
Mesh services, the success or not of Grid Information Retrieval are converted to whether Grid Services Based on Ontology can be effectively matched.And grid takes at present
Business Ontology Matching algorithm be it is considerably complicated, this is necessary when searching all kinds of relative complex services certainly, because to protect
Hinder the accuracy of service.But the lookup of some simple resources in grid, to be also converted to service.
O&M information retrieval of the invention is a kind of processing to document stem, mentions from non-structured text information
The useful information in text is taken out, is extracted according to semantic similitude, carries out the calculating of similarity, and generation one is similar
Matrix.Corresponding mapping ruler is generated according to similar matrix.Mapping ruler determines how the concept of conversion source ontology to target
In ontology.Mapping relations generally have tri- kinds of 1:1,1:n and 1:m.In addition the mapping relations of m:n can use the mapping relations of m 1:n
It is indicated to combine.Mapping ruler should include the condition for being mapped example and corresponding transfer function.Generally according to field
Concept establishes the mapping relations between the vocabulary of text and concept.In this way, just by these non-structured O&M information and structure
The domain body of change establishes connection, so as to assist to retrieve non-structured text using the knowledge of the structuring of ontology
Information.
Detailed process is as follows for O&M information retrieval method:
(1) user inputs term or phrase in search interface first, is gone to the query statement of user's input using disabling vocabulary
Fall useless function word, is only named word or related phrase that word, verb etc. are of practical significance, stem then is carried out to obtained phrase
It extracts, obtains the conceptual word or phrase that can correctly express inquiry sentence semanteme, result is passed to inquiry conversion module；
(2) the above results are searched corresponding concept by inquiry conversion module into ontology library, carry out semantization to obtained concept
Processing, including finding out the hypernym of each term, hyponym, synonym and the senses of a dictionary entry of concept, to what be can not find in ontology library
Notional word retains, and adjusts search strategy in time to return to user；
(3) it for concept matched in field ontology library, inquires conversion module and this is inquired according to gained information
Conversion makes inquiry have corresponding semantic information, then gives retrieval agent mould such as the judgement and query expansion of query semantics
Block is inquired into information bank, is inquired according to keyword match technique the inquiry that not can determine that semantic information；
(4) the customized processing module processing of resulting result is inquired, is looked into according to term original word query result, term synonym
It askes result, term hypernym query result, term hyponym query result to be ranked up, is then shown and looked by user interface
Ask result.
Advantage of the present invention is as follows:
1. service customer-centric is unfolded outward, humanized allows O&M to adapt to user；
2. allow be not in when the artificial question and answer for carrying out customer problem business and knowledge blind spot so that labor workload subtracts significantly
It is few；
3. allow manpower and physical resource reasonably with, allow O&M adapt to user demand rather than the update hardware of blindness
Resource and the investment for increasing manpower rigid to meet O&M demand；
4. pair increasing information reaches a kind of accurate integration matching retrieval, the information of knowledge base is allowed to follow trend day new
The moon is different.
Detailed description of the invention
Fig. 1 is that the intelligent knowledge integration of the Call Center O&M service platform based on ontology is illustrated with searching system.
Fig. 2 is the building process of ontology of the invention.
Fig. 3 is knowledge retrieval process frame of the invention.
Fig. 4 is that the mapping of body part information of the present invention and O&M ontology corresponds to.
Fig. 5 is the matching process that Call Center O&M service ontology of the invention combines.
Specific embodiment
The present invention is further described in detail below with reference to example.It should be appreciated that specific example described herein
It is used only for explaining the present invention, be not intended to limit the present invention.The present invention by using Call Center function then in conjunction with
The building and matching technique of Ontology, and the intelligent knowledge integration and searching system and method provided, as shown in Figure 1.
As shown in Fig. 2, the ontology of the intelligent knowledge integration and searching system of the Call Center O&M service based on ontology
Building, be using middleware will storage grid field sheet is constructed by structuring to the information in the hierarchical structure of LDAP
Body.In LDAP Tree structure, higher node indicates that relatively abstract Ontological concept, the leaf node of bottom can indicate
For more specific Ontological concept.
The present invention monitors resource dynamic using LDAP metadata information library, and essence is exactly with object technology and level
The various resources of mode display system, then monitoring information storage into LDAP information bank, so that user uses at any time, together
When for user provide the uniform logical view an of gridding resource.LDAP uses centralized management and access control in logic
System supports the distribution of resource information to store and back up, and mentions to access the resource information of the flood tide under grid environment, dynamic and isomery
Unified access mechanism is supplied.The gridding information in LDAP metadata information library uses Tree structure, with base in tree
Notebook data unit is stored in LDAP information bank, information format is as shown in Fig. 3 as entry.Wherein dn: one record
Position；Dc: one record affiliated area；Tissue belonging to ou: one record；Name/ID of cn/uid: one record.
The core protocol of platform data transmission is LDAP, for describing the bibliographic structure of gridding information, each module between platform
Data transmission, each of which leaf node all contains the metadata information for being described grid domain body concept.See own in shape
Leaf node belong to the object class GNode of the same grid, it is the subclass of empty class Top.Its LDAP association after expanding
(one kind is informal, similar to English structure, for describing for the pseudocode of the corresponding relationship of view information and grid domain body
The language of function structure chart) see annex 1.
After extending in this way, newly added project can be good at the characteristics of describing gridding resource, dynamic and real-time
It is required that must also meet.Otherneed List lists the set of properties of essential characteristic necessary to one group of grid ontology, for meeting
The integrality of grid domain body；GState describes whether the corresponding concept can be used；Source is described belonging to the corresponding concept
Node address.
As shown in Figure 4.Using Ontology Mapping technology all or part of concept in ontology in document process module
And relationship map extracts the useful information in text into O&M service ontology from non-structured text information, according to
Semantic similitude extracts, and carries out the calculating of similarity, and generate a similar matrix.It is generated according to similar matrix corresponding
Mapping ruler.Mapping ruler determines how the concept of conversion source ontology into target ontology.Namely OWL file is turned
It is melted into OWL-S file, technically specifically used Jena kit realizes the parsing of OWL file.By ontology
After the completion of building, it is stored in ontology library.
As shown in figure 5, it will be seen that document process wherein Call Center O&M information on services and Ontological concept
The general procedure of map retrieval:
1, the domain body in grid field ontology library forms ontology hierarchy chart after ontology hierarchy, each body interior also into
Row layering；
2, user search requires to generate grid field void ontology after parsing；
3, it is matched to both above-mentioned.Each node in both sides' ontology and each edge are matched respectively, calculate node
Similarity and side similarity, to calculate total similarity of both sides' ontology.Here there is the process of an iterative calculation；
4, matching result is exported；
5, in conjunction with Gstate attribute in grid domain body, come matching result determine whether to match it is available.
Call Center O&M service ontology information and the pseudo-code of the algorithm of Ontological concept map retrieval are shown in annex 2.
And for the matching that Call Center O&M service ontology in ontology combines, retrieval conversion module is believed according to gained
Breath, which retrieves this, carries out retrieval conversion, such as retrieves semantic judgement and retrieval extension, retrieval is made to have corresponding semantic information,
Then retrieval agent is given to be retrieved into information bank to not can determine that the retrieval of semantic information according to keyword match technique
It is retrieved.
User first inputs term or phrase in search interface, is removed to the retrieval sentence of user's input using disabling vocabulary
Useless function word is only named word or related phrase that word, verb etc. are of practical significance, then carries out stem pumping to obtained phrase
It takes, obtains the conceptual word or phrase that can correctly express retrieval sentence semanteme, result is passed to retrieval conversion module.
The customized processing module processing of resulting result is retrieved, according to term original word and search as a result, term synonym
Search result, term hypernym search result, term hyponym search result are ranked up, are then shown by user interface
Search result.Customized treatment resume module pseudocode is shown in annex 3, and searching algorithm pseudocode is shown in annex 4.
Annex 1: the pseudocode of the corresponding relationship of LDAP protocol information and grid domain body after expansion
Class Node Subclass of Top
{
Name//ontology name
ID // home identifier
…
Otherneed List // attribute list
Gstate // ontology state
Source // ontology mapping address
}
The matched pseudo-code of the algorithm of annex 2:Call Center O&M service ontology combination
Input: service ontology GSR and service is requested to provide ontology GSF (SP) including user
Output: meet the set of service of user's request
Matching process:
Ivlatchrnaking (GSR, GSP)
{
if(SCsim(GSR, G5P) >=Z1&&SNsim(GSR, GSP) >Z2&& SPsim(GSR, G5P) >=Z3)
Bsim (GSR, GSP) is calculated;// classification of service, the matching of service name and text description
if (Isim(GSR, GSP) >=Z4&&Osim(GSR, GSP) >=Z5&&Psim(GSR, GSP) >=Z6
&&Esim (G5R, G5P) >=Z7) //Z1 to Z7 is all respective threshold
IOPEsimGSR, GSP.;The matching of //IOPE
Qsim ( GSR, GSP) ;The matching of //Qos
Zsim (GSR, GSP);The calculating of // comprehensive similarity matches
If(Zsim(GSR,GSP)>=S1
(matchset.append(spService);If // matched service is met the needs of users, which is added
Into services set,
)
Else // it fails to match, then return to fail.
return fail;
}
}
// before return, the descending arrangement of similarity provided is requested and serviced according to user
Matchsetresult = Mathcsort(matchset);// arranged according to the size descending of similarity
return Matchsetresuit;
}
Annex 3: customized treatment resume module pseudocode
Struct Concept
{char number[];// conceptual sense classification code
char name[];The description of // conceptual sense
int hypernum;// upperseat concept number
int hyponnum;// subordinate concept number
int synonnum;// peer concept number
int relnum;// related notion number
struct Concept *hypernym;The pointer of // direction upperseat concept
struct Concept *hyponym;The pointer of // direction subordinate concept
struct Concept *synonym;The pointer of // direction concept at the same level
struct Concept *relation;The pointer of // direction related notion
}
Annex 4: searching algorithm pseudocode
Begin
If Conceptmatching then
QueryExpansion ((ql',q2',···, q;'));// extension (ql', q2' ..., q;') about
The concept of synonym, semanteme implies and extension, semantic relation;According to corresponding relationship, the result retrieved；
Feedback (Nconceptmatchingl);
Endif
If Nconceptmatching2 }} then
Calculate the similarity between (qi+i ", qi+2 " ..., qn ") and (Wl, W2,
..., Wn)
Feedback(Nconceptmatching2);
Endif
End
Claims (5)
1. a kind of intelligent knowledge of Call Center O&M service platform based on ontology is integrated and searching system, feature exist
In, comprising: document processor inquires conversion module, acts on behalf of retrieval module, customized treatment module, user interface and ontology library
And information bank；Wherein:
The user interface is used for user input query sentence；And show query result；
The document processor, for handling the data transmitted from data source, including, O&M and use are given to data source
Text conversion in document is word, logarithm firstly, carrying out the lexical analysis of text by each information point in the information bank of family
Word, hyphen, punctuate and letter capital and small letter handled；Then, removed in O&M and user information using disabling vocabulary
Function word filters out those and acts on little word for retrieval, is only named word, the word or phrase that verb is of practical significance；Then,
Stem extraction is carried out to obtained phrase, removes front and back and sews, so that the grammer variation word of query term can also be retrieved；Then,
Index entry is selected, determines which word or stem, phrase are used as index element, obtains the conceptual word that can correctly express literature content
Or phrase；The mapping relations between the vocabulary of text and concept are established according to the concept in field, so that these are non-structured
O&M information and the foundation of the domain body of structuring contact, and assist to retrieve using the knowledge of the structuring of ontology non-structured
Text information；Finally, storing analysis result into field ontology library and information bank；
The inquiry conversion module, corresponding concept is searched according to the above results into ontology library, carries out language to obtained concept
Adoptedization processing；And according to concept matched in domain body, inquiry conversion is carried out to this inquiry according to gained information, according to
The user query sentence that family interface is transmitted carries out inquiry conversion to this inquiry according to information, comprising: the judgement of query semantics and
Query expansion makes inquiry have corresponding semantic information；And retrieval agent module is given these information；
It is described to act on behalf of retrieval module, it according to the information that transmits of inquiry conversion module, is inquired into information bank, to not can determine that
The inquiry of semantic information is inquired according to keyword match technique；It inquires resulting result and passes to customized treatment resume module；
The customized treatment module, according to term original word query result, term synonym query result, term hypernym
Query result, term hyponym query result are ranked up, and user interface is then transferred to show query result；
The ontology library, for storing the O&M Information Ontology of building, O&M Information Ontology includes the correlation of Domain-specific ontology
Knowledge also includes the information of the various services provided；
Described information storehouse, as ontology library, for storing the O&M Information Ontology of building；
The query statement that user is inputted by user interface obtains the conceptual word or phrase that can correctly express inquiry sentence semanteme,
Result is passed to inquiry conversion module, and searches corresponding concept into ontology library according to the above results, to obtained concept
Carry out semantization processing, for concept matched in domain body, inquire conversion module according to gained information to this inquire into
Row inquiry conversion, then gives retrieval agent module and is inquired into information bank, to not can determine that the inquiry of semantic information by
It is inquired according to keyword match technique；The customized processing module processing of resulting result is inquired, is inquired according to term original word
As a result, term synonym query result, term hypernym query result, term hyponym query result are ranked up,
Then query result is shown by user interface.
2. intelligent knowledge integration according to claim 1 and searching system, which is characterized in that the building O&M information
Ontology is based on following rule:
(1) ability of Call Center O&M service platform is given full play to
The structuring capacity of O&M itself is given full play to, including uses UDDI registration information and LDAP information to construct O&M sheet
Body；
(2) sufficiently multiplexing
After establishing domain body, O&M Information Ontology is constructed using domain body, gives full play to the multiplexing of O&M domain body
Ability；
(3) body size appropriateness
For O&M ontology on the basis of giving full expression to semantic information, the concept number for including in ontology should be minimum as far as possible
Change, as far as possible by redundancy removal.
3. intelligent knowledge integration according to claim 1 or 2 and searching system, which is characterized in that the building O&M letter
Ontology is ceased, including gets data from data source, passes data to document processor；Document processor is to the given fortune of data source
Each information point in dimension and user information database；Firstly, carrying out the lexical analysis of text, i.e., it is by the text conversion in document
Word handles the capital and small letter of number, hyphen, punctuate and letter, then removes O&M using disabling vocabulary and user believes
Function word in breath filters out those and acts on little word for retrieval, is only named word, the word or word that verb is of practical significance
Group；Then stem extraction is carried out to obtained phrase, removes front and back and sews, so that the grammer variation word of query term can be also detected
Rope；Then index entry is selected, determines which word or stem, phrase are used as index element, acquisition can correctly express literature content
Conceptual word or phrase；Finally analysis result is stored into field ontology library and information bank.
4. intelligent knowledge integration according to claim 1 or 2 and searching system, which is characterized in that inquiry conversion module,
Data query and communication between retrieval agent module and ontology library information bank, using ldap protocol；By LDAP directory service
Technology come monitor resource dynamic, that is, use object technology and hierarchical fashion display system various resources, then monitoring information is deposited
It stores up in platform information library, so that user uses at any time, while providing the uniform logical view an of gridding resource for user；
Centralized management and access control are used in LDAP server logic, the distribution of resource information is supported to store and back up, to visit
Ask that the resource information of the flood tide under grid environment, dynamic and isomery provides unified access mechanism.
5. a kind of intelligent knowledge integration and search method based on system described in one of claim 1-4, which is characterized in that specific
Steps are as follows:
(1) user inputs term or phrase in search interface first, is gone to the query statement of user's input using disabling vocabulary
Fall useless function word, is only named word or related phrase that word, verb etc. are of practical significance, stem then is carried out to obtained phrase
It extracts, obtains the conceptual word or phrase that can correctly express inquiry sentence semanteme, result is passed to inquiry conversion module；
(2) the above results are searched corresponding concept by inquiry conversion module into ontology library, carry out semantization to obtained concept
Processing, including finding out the hypernym of each term, hyponym, synonym and the senses of a dictionary entry of concept, to what be can not find in ontology library
Notional word retains, and adjusts search strategy in time to return to user；
(3) it for concept matched in field ontology library, inquires conversion module and this is inquired according to gained information
Conversion makes inquiry have corresponding semantic information, then gives retrieval agent mould such as the judgement and query expansion of query semantics
Block is inquired into information bank, is inquired according to keyword match technique the inquiry that not can determine that semantic information；
(4) the customized processing module processing of resulting result is inquired, is looked into according to term original word query result, term synonym
It askes result, term hypernym query result, term hyponym query result to be ranked up, is then shown and looked by user interface
Ask result.
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