CN104637371B - A kind of method being embedded into ontologies in game model - Google Patents

Abstract

The present invention relates to game Virtual Learning technical field, more particularly to a kind of method being embedded into ontologies in game model.The method includes building the ontologies of object game；According to type of play and constitution element, the game atom challenge ontology model of game model is built；The similarity of body is challenged in specific knowledge set with each described game atom in calculating the ontologies, and according to the similarity, sets up the mapping that the knowledge collection challenges body to each game atom；Choose and challenge model as the game atom being adapted to knowledge collection similarity highest game atom challenge body.The present invention carries out unified representation based on body to domain knowledge and game, and essence association therebetween is analyzed by calculating body similarity, realizes the automatic adaptation of knowledge and game, reduces the individual subjective impact of designer.

Description

A kind of method being embedded into ontologies in game model

Technical field

Ontologies are embedded into game model the present invention relates to game Virtual Learning technical field, more particularly to one kind In method.

Background technology

Educational games fast development simultaneously achieves good achievement, its design field it is universal around core concept be：Trip The design of play needs the participation for playing and educating two fields to participate.But for a long time, design amusing products game and The education for conveying knowledge belongs to two entirely different industries, each using different mentality of designing and construction method, therefore It is extremely difficult to the balance of " educational " and " recreational ".

In terms of design of the education game, Waraich emphasize a significant study must effectively story background and The overall process that motivation learns to promote learner to complete.Kristian proposes a kind of design of the education game frame tested based on fluid Frame, the method by teaching elements such as instructional objective, the contents of courses by participating in and feedback is added to during the fluid of game tests, Allow learner in gaming with problem, learning cognition is completed by completing Mission Objective.

Fusion method on knowledge with game, some scholars build trip from this body structure of knowledge and feature Knowledge model in play is attempted in knowledge insertion game.Brunot proposes a kind of knowledge based signature analysis and knowledge classification Cognitive model, learning activities and learner's thought process are described using Object-oriented Technique, and cognitive process is entered with game link Row depth is combined.Miroslav proposes that a kind of learning object that is based on creates education resource fragment, and then balances intellectual and game The knowledge model of property；Use UML (Unified Modeling Language, UML) and extensible markup language (Extensible Markup Language, XML) comes design games and knowledge meta-model, game meta-model concept is introduced and is ground Study carefully field.

A large number of researchers have carried out a series of researchs, the mainly design including macroscopic aspect of current achievement regarding to the issue above Instruct theory, reference method or be related to the empirical model of microcosmic game element design.But in actual design operation, do not occur Generally acknowledged formalization method or template is instructed, and is not more formed with objective law or theorem, as reference, with universality Method for normalizing or automated tool.Therefore in most cases, designer or developer still need to carry out more subjectivity to create again Make, to exploitation designer require it is higher, should correct understanding domain knowledge intension, again be familiar with game substantive characteristics and Method for designing.And in actual design and development process, often the deviation and scarcity of knowledge understanding easily cause " educational " or " section The property learned " missing fails to agree with the original intention of design of the education game；Or cause whole game " amusement because game design is lacked experience Property " not strong, it is allowed to be more closely similar to a teaching software, it is impossible to reach the purpose of lasting attraction participant；Or " educational " and " joy The forced combination of happy property ", makes game experiencing and learning link turn into two completely isolated processes, has both destroyed game overall experience Certain interest is lost, while also have impact on final results of learning.

The content of the invention

The technical problem to be solved in the present invention there is provided one kind and domain knowledge and game mechanism carried out into automatic adaptation simultaneously The method of fusion.

In order to solve the above-mentioned technical problem, the invention provides a kind of side being embedded into ontologies in game model Method, comprises the following steps：

Build the ontologies of object game；

According to type of play and constitution element, game atom challenge body is built；

The similarity that the ontologies challenge body with each described game atom is calculated, and according to the similarity, Set up the mapping that specific knowledge body collection in the ontologies challenges body to atom of being played each described；

Choose with described in the specific knowledge body collection similarity highest play atom challenge body as with the spy Determine the game atom challenge body body of ontologies collection adaptation.

Preferably, calculation knowledge body includes with the specific steps of the similarity of atom challenge body of being played each described：

In the ontologies, the specific knowledge body collection to be mapped is selected；

Compare the number and concept in each described game atom challenge body of the specific knowledge body centralized concept class The number of class, the similarity is set to 0 if difference, otherwise carries out next step calculating；

Calculation knowledge body challenges the comprehensive similarity of body with each described game atom.

Preferably, the specific knowledge body collection includes information, the letter of the first concept classes relation of the first concept class Breath, pass between the information of the first event class, the information of the first event classes relation and the first concept class and the first event class The information of system.

Preferably, the information of the game atom challenge body including the second concept class, the second concept classes relation Between information, the information of second event class, the information of second event classes relation and the second concept class and second event class The information of relation.

Preferably, the comprehensive similarity is obtained as follows：

The comprehensive similarity is similarity, the first event class of the first concept class and the second concept class It is similar with the similarity of the second event class, the first concept classes relation and the second concept classes relation The similarity and the first concept class of degree, the first event classes relation and the second event classes relation With the first event classes relation and the product of the similarity of the second concept class and second event classes relation.

Preferably, the similarity is calculated according to following method：

Description collection respectively A, B of the first concept and the second concept are set, then the first concept a's and the second concept b is similar Degree is calculated by below equation and tried to achieve：

Wherein, A ∩ B represent the common factor of description collection A and B, and A/B represents the difference set of description collection A and B, and α (a, b) is first general The depth function of a and the second concept b is read, is calculated by below equation and tried to achieve：

Wherein, 0≤α≤1, depth (a) represents the shortest path distance from the first concept a to root node；Depth (b) tables Show the shortest path distance from the second concept b to root node；First concept is between the information of the first concept class, the first concept class The information of relation, the information of the first event class, the information of the first event classes relation or the first concept class and the first event class Between relation information, corresponding second concept be the information of the second concept class, the information of the second concept classes relation, The letter of the information, the information of second event classes relation or the second concept class and second event classes relation of second event class Breath.

Preferably, it is synset, feature set or semantic neighbours' collection that the description integrates.

Preferably, the mapping includes class mapping and relationship map；The class mapping includes：Mapping between concept class, Mapping between event class；The relationship map includes：The mapping of concept classes relation, the mapping of event classes relation, The mapping of concept class and event classes relation.

Above-mentioned technical proposal of the invention has the following advantages that：What the present invention was provided is embedded into game model by ontologies In method unified representation is carried out to domain knowledge and game based on body, and analyze two by calculating body similarity Essence association between person, realizes the automatic adaptation of knowledge and game.The individual subjective impact of designer is reduced, due to field The problems such as shortage of knowledge causes " educational " missing or " recreational " missing is caused because game design is lacked experience.Together When, the establishment of game challenge ontology library and domain knowledge body frame realizes shared and game of the knowledge between different game Shared mechanism of the framework under different application field, improves the validity of design.

Brief description of the drawings

Fig. 1 is method design concept schematic diagram provided in an embodiment of the present invention；

Fig. 2 is the method flow diagram that the present invention implements to provide；

Fig. 3 is method and technology solution schematic diagram provided in an embodiment of the present invention；

Fig. 4 is ontologies block schematic illustration provided in an embodiment of the present invention；

Fig. 5 is game challenge ontology model schematic diagram provided in an embodiment of the present invention；

Fig. 6 is Knowledge Set provided in an embodiment of the present invention and game atom challenge body similarity computing block diagram；

Fig. 7 is Knowledge Set provided in an embodiment of the present invention and game atom challenge body similarity computational methods flow chart；

Fig. 8 is child's knowledge concepts provided in an embodiment of the present invention and hierarchical structure schematic diagram.

Specific embodiment

Specific embodiment of the invention is described in further detail with reference to the accompanying drawings and examples.Following examples For illustrating the present invention, but it is not limited to the scope of the present invention.

The present invention provide the method design concept being embedded into ontologies in game model be, by creation process that This is related but enters from different field element (mainly including domain knowledge, technical ability main points, game element and rule mechanism etc.) Row unified quantization research, and internal essence correlation is analyzed to realize the mapping between knowledge and game mechanism.As shown in figure 1, It is method design concept schematic diagram provided in an embodiment of the present invention.The source of " game " is challenged for game, therefore knowledge and trip The depth integration of domain knowledge and game challenge is realized in the fusion of play.Meanwhile, domain knowledge and game challenge are general Read in aspect closer to the possibility of both realizations depth integration is bigger and with more actual operation.Treated for infinite The content that conveys knowledge game challenge type is limited, therefore the similarity that the method for providing of the invention has carried out finite number of time is commented Estimate, optimal Adaptation Options can be obtained.

As shown in Fig. 2 being the method flow diagram implemented and provide of the invention.The method includes：Build the knowledge of object game Body frame；According to type of play and constitution element, the game atom challenge body of game model is built；According to ontologies with Game atom challenges the calculating of body similarity, realizes that ontologies challenge the mapping of body to game atom；Obtain and knowledge The game atom challenge body of ontology knowledge content adaptation.

Further, as shown in figure 3, being method and technology solution schematic diagram provided in an embodiment of the present invention.By knowledge The method that body is embedded into game model is specifically included：

(1) the relevant knowledge classification in analysis knowledge engineering field, builds object game and knowledge content is formalized The ontologies framework of expression is as shown in Figure 4.

(2) type of play and constitution element are analyzed, game general element model is built, and according to classical Mission Objective Challenge mechanism builds game atom challenge disaggregated model.On game atom challenge disaggregated model concept hierarchy, formalized Represent that structure game atom challenge body is as shown in Figure 5.Wherein, game challenge is the source of " game ", and game challenge is by more Individual different game atom challenge is constituted, and game atom challenge body is the formalization representation mode of game atom challenge.

(3) two isomery bodies of analysis are the sheet between ontologies and game atom challenge body in structure and semantically Matter is associated, and the automatic mapping played between atom challenge and ontologies framework is realized by calculating the similarity of the two i.e. Ontologies have been embedded into game model.

(4) it is comprehensive by all game atom challenge bodies in all ontologies collection in ontologies framework and game challenge The calculating of similarity is closed, the game atom challenge body being adapted with each ontologies collection is obtained.It is former according to the game for obtaining Son challenge body, further constructs the task of game challenge and then embodies " game ".

Further, as shown in fig. 7, being Knowledge Set provided in an embodiment of the present invention and game atom challenge body similarity Computational methods flow chart.The calculating of body similarity is challenged with game atom according to ontologies, realizes ontologies described in The specific steps of the mapping of game atom challenge body include：Knowledge based body frame, builds ontologies collection to be mapped； Compare the number of ontologies collection and game atom challenge Ontological concept class (name part of speech)；Calculation knowledge body collection and game atom Challenge body comprehensive similarity, by clustering procedure carry out ontologies collection and game atom challenge body between class map and Relationship map.Wherein, class mapping includes：Mapping between concept class is the mapping between name part of speech and name part of speech, event class it Between mapping be mapping between verb class and verb class；Relationship map includes：The mapping of concept classes relation is a part of speech Between relation mapping, the mapping of event classes relation is the mapping of verb classes relation, between concept class and event class The mapping of relation is the mapping of relation between verb and noun.

Further, both similarities are calculated using Tvorsky models.Assuming that in body O1 in concept a and body O2 Concept b is described collection, such as synset, feature set or semantic neighbours' collection.The present invention is based on Chinese thesaurus structure concept The synset of a, b collects as description, and use A, and B is represented, i.e. A=syn (a), B=syn (b).Wherein, A ∩ B represent A and B Common factor, A/B represents the difference set of A and B, and the similarity of concept a and b can be calculated by below equation try to achieve：

Wherein, α (a, b) is two functions of concept depth, can be calculated by below equation and tried to achieve：

Wherein, 0≤α≤1, depth (a) represents the shortest path distance from concept a to root node.

Therefore, the comprehensive similarity computing formula between ontologies collection and game atom challenge body is as follows：

SIM (KnSetK, ChallModt)=Num_NounClass_Match (KnSetK, ChallModt) * SIM1* SIM2*SIM3*SIM4*SIM5 (3)

Wherein,

Further, as shown in fig. 6, being Knowledge Set provided in an embodiment of the present invention and game atom challenge body similarity Computing block diagram.When ontologies collection is identical with the number of game atom challenge Ontological concept class, comprehensive similarity is concept class The similarity SIM2's between similarity SIM1, event class (verb class), concept classes relation between (name part of speech) is similar Degree SIM3, the similarity SIM4 and concept class of relation (relation object) and event classes relation between event class (verb class) The product of similarity SIM5；When ontologies collection is different from the number of game atom challenge Ontological concept class, comprehensive similarity It is zero.It is presently believed that as long as both core name part of speech numbers are different, then similarity is 0.The SIM1 of calculating, SIM2, SIM3, Any one similarity of SIM4 or SIM5 is 0, then comprehensive similarity is 0.Therefore the calculation process for calculating comprehensive similarity is optimized for, When the result of calculation of certain factor similarity is 0, calculating process terminates.

Further, the above method tries to achieve similarity between the corresponding game atom challenge body of ontologies collection Calculate, in order to all game atoms for obtaining being adapted with certain selected ontologies collection in ontologies framework challenge this Body is, it is necessary to calculate the comprehensive similarity between all game atoms challenge body in the ontologies collection and game challenge.Cause Game atom challenges Limited Number (20~30) at this stage, and then ontologies collection challenges the priority of similarity with game atom Order can't influence to be embedded into ontologies in game model, therefore the embodiment of the present invention does not consider ontologies collection and institute There is game atom to challenge the sequencing problem of similarity between body.The corresponding form of knowledge model represents ontologies framework, trip Play property is completed by game challenge, and game atom challenge composition game challenge, game atom ontology model form represents game atom Challenge；Framework is a structure, just as an empty table, loads and ontologies have been reformed into after knowledge content, knowledge Body includes multiple ontologies collection.

Further, during comprehensive similarity is calculated, it is related to given threshold to judge that comprehensive similarity result is The no problem for corresponding to actual needs, wherein, the threshold value of setting is typically based primarily upon subjective experience and is screened.Likewise, because existing Stage game atom challenge Limited Number (20~30), for each the ontologies collection in ontologies framework with multiple Game atom challenge body carries out the calculating of comprehensive similarity, and the corresponding game atom challenge being adapted with ontologies collection During body number is less (being less than 20~30), therefore given threshold is calculated for the comprehensive similarity in the embodiment of the present invention The influence of screening is negligible.

The embodiment of the present invention is chosen to interesting and knowledge as a example by towards the cognitive educational games system of preschool child Property require preschool child's Cognitive education field all higher, with children's color, figure, logic, letter, science and technology and society's general knowledge Target is perceived as, design craps game form is attempted.Wherein, logic cognition is divided into the concept cognition of figure, color identification, figure Identification, the local cognition with whole relation；It is cognitive and upper and lower case letter association recognize that language cognition is divided into English alphabet Know；Naturally scientific and technological cognition is divided into animal cognition, the cognition that animal associates with food, living environment；Social general knowledge cognition is divided into state Family's concept is cognitive, country and national flag, identifies the cognition that building, dress ornament etc. are associated；Daily living article cognition is divided into daily life The cognition of the various things in work.Ontologies are embedded into the tool in game model for preschool child's Cognitive education field Gymnastics is made as follows：

(1) ontologies framework is set up according to above-mentioned perception target, is further illustrated in figure 8 ontologies framework Interior concept class and hierarchical structure, are as shown in table 1 the relation and attribute structure of concept class in ontologies framework.

The child's ontologies concept class relation of table 1 and attribute

(2) body is challenged with each atom of playing in game challenge by each the ontologies collection in calculation knowledge body Between comprehensive similarity, choose adaptation game atom challenge body so that build game challenge.Specifically, ontologies collection Five yuan of formulas are defined as：KnowlegeSet={ NounClass, N_Class_Re, VerbClass, V_Class_Re, N_V_Re }, NounClass, N_Class_Re, VerbClass, V_Class_Re, N_V_Re are represented closed between concept class, concept class respectively System, the relation between event class, event classes relation and concept class and event class.It is generally general during specific practical operation Read class to run after fame part of speech, event class takes its main actions, i.e. verb class.

For example, to represent the relation between " country " and " national flag ", five yuan of formulas of its ontologies collection are represented by：

{ { country, national flag }, { mark/flagged }, { }, { }, { } }, i.e., comprising two name parts of speech " country " and " national flag ", Its relation is " mark " or " flagged ".This ontologies collection without event, behind three be expressed as sky.

For another example, to represent the Predatory relation between " cat " and " fish ", five yuan of formulas of its ontologies collection are represented by：

{ { cat, fish }, { predation/prey }, { }, { }, { } }, i.e., comprising two name parts of speech " cat " and " fish ", its relation is " predation " or " prey ".This ontologies collection without event, behind three be expressed as sky.

Compare ontologies collection class capacity and each game atom challenge body name part of speech number, it is found that most of intelligence classes are former Son challenge and its number matches.

Calculate name part of speech similarity：To concept class semanteme without constraint, it is 1 to give tacit consent to its similarity to the challenge of intelligence class atom.Cause This part of speech relation Similarity Measure draws：

SIM (KS1, Chall-Mapping)=0.8,

SIM (KS1, Chall-Distribution)=0.3,

……

SIM (KS1, Chall-Action)=0,

SIM (KS1, Chall-Stratege)=0,

……

I.e. the ontologies collection challenges body similarity with " intelligence challenge " --- " relation " --- " mapping " game atom It is 0.8, is 0.3 with " intelligence challenge " --- " relation " --- " distribution " game atom challenge body similarity, remaining action class, Policy class challenge similarity is 0.According to Similarity Measure end value, descending row is carried out to above-mentioned all game atom challenge bodies Sequence：Mapping --- distribution --- ...

Previously according to practical experience value given threshold 0.5, it is phase to show that " intelligence " challenges " mapping " in subclass " relation " Like degree highest game atom challenge body.

(3) based on above-mentioned adaptation atom challenge ontology model, and obtained according to Similarity Measure and ontologies All game atoms challenge body of collection fit height sequence, provides task level game challenge and recommends.Selected ontologies frame Other ontologies collection in frame, carry out same operation and draw all game atoms challenge body for mapping therewith, provide corresponding Task level game challenge recommend.By the challenge Ontology integration game challenge of the game atom of all adaptations, with other challenges as " when Between pressure " etc. be combined, constitute such as " infant cognition is seen repeatedly " intelligence development class play.

Further, " infant cognition is seen repeatedly " adjusts the complete matched rule of figure with reference to traditional " seeing game repeatedly " It is whole for logic association or mapping, just realize that two icon lines with correlation are eliminated.Game content module includes 1) identical Color icon matches are eliminated；2) similar fitgures icon matches are eliminated；3) animal and its food icon matches are eliminated；4) entirety and office Portion's icon matches are eliminated；5) upper and lower case letter icon matches are eliminated；6) country matches elimination with flag icon.Each module is designed 10 outposts of the tax office, each outpost of the tax office provides 20 10 pairs of icons with one-to-one relationship.Using operating under IPAD environment, use Family carries out man-machine interaction by touch manner.

In sum, the method being embedded into ontologies in game model that the present invention is provided is based on body to neck Domain knowledge carries out unified representation with game, and essence association therebetween is analyzed by calculating body similarity, realizes knowing Know the automatic adaptation with game.The individual subjective impact of designer is reduced, because the shortage of domain knowledge is caused " educational " The problems such as lacking or cause " recreational " missing because game design is lacked experience.Meanwhile, game challenge ontology library and field The establishment of ontologies framework realizes shared and game frame of the knowledge between different game under different application field Shared mechanism, improves the validity of design.

Finally it should be noted that：The above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although The present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those within the art that：It still may be used Modified with to the technical scheme described in foregoing embodiments, or equivalent is carried out to which part technical characteristic； And these modification or replace, do not make appropriate technical solution essence depart from various embodiments of the present invention technical scheme spirit and Scope.

Claims (3)

1. a kind of method being embedded into ontologies in game model, it is characterised in that comprise the following steps：

Build the ontologies of object game；

According to type of play and constitution element, game atom challenge body is built；

Calculate the ontologies and challenge the similarity of body with each described game atom, and according to the similarity, set up Specific knowledge body collection challenges the mapping of body to atom of being played each described in the ontologies；

Choose and specific know as with described with atom challenge body of being played described in the specific knowledge body collection similarity highest Know the game atom challenge body of body collection adaptation；

Wherein, calculation knowledge body includes with the specific steps of the similarity of atom challenge body of being played each described：

In the ontologies, the specific knowledge body collection to be mapped is selected；

Compare the number and concept class in each described game atom challenge body of the specific knowledge body centralized concept class Number, the similarity is set to 0 if difference, otherwise carries out next step calculating；

Calculation knowledge body challenges the comprehensive similarity of body with each described game atom；

Wherein, the specific knowledge body collection includes information, information, first of the first concept classes relation of the first concept class The letter of the information of event class, the information of the first event classes relation and the first concept class and the first event classes relation Breath；

The game atom challenge body includes information, the information of the second concept classes relation, second thing of the second concept class The information of the information, the information of second event classes relation and the second concept class and second event classes relation of part class；

The comprehensive similarity is obtained as follows：

The comprehensive similarity is similarity, the first event class and the institute of the first concept class and the second concept class State the similarity of second event class, the similarity of the first concept classes relation and the second concept classes relation, The similarity and the first concept class of the first event classes relation and the second event classes relation and the The product of the similarity of one event classes relation and the second concept class and second event classes relation；

The similarity is calculated according to following method：

Set description collection respectively A, B of the first concept and the second concept, then the similarity of the first concept a and the second concept b by Below equation is calculated and tried to achieve：

$Sim\left(a,b\right)=\frac{|A\∩B|}{|A\∩B|+\mathrm{\α}\left(a,b\right)|A/B|+\left(1-\mathrm{\α}\left(a,b\right)\right)|B/A|}---\left(1\right)$

Wherein, A ∩ B represent description collection A and B common factor, A/B represent description collection A and B difference set, α (a, b) be the first concept a and The depth function of the second concept b, is calculated by below equation and tried to achieve：

$\mathrm{\α}\left(a,b\right)=\left\{\begin{array}{cc}\frac{depth\left(a\right)}{depth\left(a\right)+depth\left(b\right)},& depth\left(a\right)\≤depth\left(b\right)\\ 1-\frac{depth\left(a\right)}{depth\left(a\right)+depth\left(b\right)},& depth\left(a\right)>depth\left(b\right)\end{array}\right.---\left(2\right)$

Wherein, 0≤α≤1, depth (a) represents the shortest path distance from the first concept a to root node；Depth (b) represent from Shortest path distances of the second concept b to root node；First concept is the information of the first concept class, the first concept classes relation Information, between the information of the first event class, the information of the first event classes relation or the first concept class and the first event class The information of relation, corresponding second concept is the information of the second concept class, information, second of the second concept classes relation The information of the information, the information of second event classes relation or the second concept class and second event classes relation of event class.

2. the method being embedded into ontologies in game model according to claim 1, it is characterised in that the description Integrate is synset, feature set or semantic neighbours' collection.

3. the method being embedded into ontologies in game model according to claim 2, it is characterised in that the mapping Including class mapping and relationship map；The class mapping includes：Mapping between concept class, the mapping between event class；The pass It is that mapping includes：The mapping of concept classes relation, the mapping of event classes relation, concept class and event classes relation Mapping.