CN106326422A - Method and system for retrieving food security data information based on knowledge ontology - Google Patents
Method and system for retrieving food security data information based on knowledge ontology Download PDFInfo
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- CN106326422A CN106326422A CN201610720106.8A CN201610720106A CN106326422A CN 106326422 A CN106326422 A CN 106326422A CN 201610720106 A CN201610720106 A CN 201610720106A CN 106326422 A CN106326422 A CN 106326422A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2452—Query translation
- G06F16/24522—Translation of natural language queries to structured queries
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
- G06F40/284—Lexical analysis, e.g. tokenisation or collocates
Abstract
The embodiment of the invention provides a method and a system for retrieving food security data information based on knowledge ontology. The method comprises the following steps of firstly, building a food security knowledge ontology base, wherein the food security knowledge ontology base comprises a food knowledge ontology and a relation object, and the relation object is used for correlating at least one pair of food knowledge ontology; then, according to a query string inputted by a user, respectively processing under the different conditions; when the query string is a natural language, segmenting the words, so as to obtain the word segmenting result; according to the word segmenting result, determining the combination of food knowledge ontology and relation object; according to the combination of food knowledge ontology and relation object in the food security knowledge ontology base, determining the query object; according to the query object, obtaining the query result; finally, returning the query result back to a user. The method has the advantage that the problem of the user failing to accurately find the resources related with demand is solved.
Description
Technical field
The present invention relates to technical field of information retrieval, particularly relate to the food safety data letter of a kind of knowledge based body
The method and system of breath retrieval.
Background technology
Along with widely available in people's lives of network technology, the extensive raising of social informatization degree, every field
The information resources accumulated are being skyrocketed through.For field of food safety, food safety Regulation department produces substantial amounts of food
Product safety detection data, individual data the most only illustrates the situation of certain element (hazardous material) in the sample being detected, but in a large number
Abundant food security information has been contained in the set of data.
Nowadays, the mode that major search method is index key of search engine, user is to pass through index key
Inquire about food security information.
When inventor applies in first technology, find in terms of food security information precision ratio, have the biggest owing in first technology
Lacking, although internet data information is many, but lack contact between these information, message structure is loose, and owing to user inquires about
The diversification of forms of food safety data, computer is difficult to the reason such as natural language of complexity, causes the user cannot be accurate
Find the resource relevant to demand.
Summary of the invention
In view of the above problems, it is proposed that the present invention in case provide one overcome the problems referred to above or at least in part solve on
State the method for the food safety data information retrieval of the knowledge based body of problem and the food peace of corresponding knowledge based body
The system of full data information retrieval.
According to one aspect of the present invention, it is provided that the side of the food safety data information retrieval of a kind of knowledge based body
Method, including:
Structuring food prods security knowledge ontology library；Described Food Safety Knowledge ontology library includes food ontologies and relation pair
As；At least one pair of food ontologies is associated by described relationship object；Wherein, described relationship object includes class relations object,
The food ontologies in generic food ontologies with father and son's hierarchical relationship is associated by described class relations object；No
Non-class relations object is used to be associated between generic food ontologies；
Receive the query string of client input；
Judge that described query string is key word, key word combination or natural language；
If described query string is key word, then described key word is mated with Food Safety Knowledge ontology library, obtain
Obtain Query Result；
If described query string is crucial contamination, then according to this key contamination determine food ontologies with
The combination of relationship object；
If described query string is natural language, then described query string is carried out participle, obtain word segmentation result, and according to dividing
Word result determines the combination of food ontologies and relationship object；
Based on described food ontologies and the combination of relationship object, know according to the food in Food Safety Knowledge ontology library
Know body and the combination of relationship object, determine query object, and obtain Query Result according to described query object；
Described Query Result is returned to client.
Alternatively, after the step of described structuring food prods security knowledge ontology library, also include:
Receive user the renewal of Food Safety Knowledge ontology library is operated；Described renewal operation includes: pacify described food
Omniscient know exist between food ontologies and/or the food ontologies in ontology library the interpolation of relationship object, amendment and
Delete.
Alternatively, described described query string is carried out participle, obtain word segmentation result, and determine that food is known according to word segmentation result
Know body and the combination of relationship object, including:
Described query string is carried out participle, and utilizes concept class dictionary and relation object dictionary to determine each participle in word segmentation result
Part of speech；Described part of speech includes food ontologies part of speech and relationship object part of speech；
By participle and the participle of relationship object part of speech of food ontologies part of speech, be combined as described food ontologies and
The combination of relationship object.
Alternatively, described based on described food ontologies and the combination of relationship object, according to Food Safety Knowledge body
Food ontologies in storehouse and the combination of relationship object, determine query object, including:
The participle of the food ontologies in query string is entered with the food ontologies in Food Safety Knowledge ontology library
Row coupling；
If the participle of food ontologies matches with the food ontologies of Food Safety Knowledge ontology library, then record
The food ontologies matched is highest similarity, and calculates this food ontologies and Food Safety Knowledge ontology library its
The first similarity between his food ontologies；
For the relationship object associated by each food ontologies, calculate its food ontologies corresponding with query string
The second similarity between corresponding relationship object；
The second similarity by the first similarity of food ontologies Yu the relationship object being related to this food ontologies
It is multiplied, it is thus achieved that total similarity that food ontologies combines with relationship object；
Select N number of combination that food ontologies is forward with total sequencing of similarity of relationship object combination, search its inquiry
Object.
Alternatively, described based on described food ontologies and the combination of relationship object, according to Food Safety Knowledge body
Food ontologies in storehouse and the combination of relationship object, determine query object, also include:
If the participle of food ontologies does not matches with the food ontologies of Food Safety Knowledge ontology library, the most right
Described word segmentation result is extended, and obtains the expanded set of corresponding each food ontologies, and described expanded set includes at least one
The food ontologies of individual extension；
The food ontologies of each extension is mated with the food ontologies in Food Safety Knowledge ontology library；
If the food ontologies of extension matches with the food ontologies of Food Safety Knowledge ontology library, then record
The food ontologies matched is highest similarity, and calculates this food ontologies and Food Safety Knowledge ontology library its
The first similarity between his food ontologies；
For the relationship object associated by each food ontologies, calculate between itself and the participle with relationship object
Second similarity；
The second similarity by the first similarity of food ontologies Yu the relationship object being related to this food ontologies
It is multiplied, it is thus achieved that total similarity that food ontologies combines with relationship object；
Select N number of combination that food ontologies is forward with total sequencing of similarity of relationship object combination, search its inquiry
Object.
Alternatively, the described step that described Query Result is returned to client, including:
By N number of food ontologies forward for total sequencing of similarity and the another one food associated by the combination of relationship object
The information of product ontologies returns to client.
Alternatively, this food ontologies of described calculating and other food ontologies of Food Safety Knowledge ontology library
Between the step of the first similarity, including:
Utilize formula (1)
Calculate first between other food ontologies of this food ontologies and Food Safety Knowledge ontology library
Similarity；Wherein, described t1 is the food ontologies matched, and t2 is that other food of Food Safety Knowledge ontology library is known
Knowing body, n is the hierarchical depth in t1 and t2 hierarchical relationship in Food Safety Knowledge ontology library；δi(t1,t2) it is in level
When the degree of depth is i, the parent relation value between t1 and t2, whereinθiIt is
Weight.
According to another aspect of the present invention, it is provided that the food safety data information retrieval of a kind of knowledge based body
System, including:
Build module, for structuring food prods security knowledge ontology library；Described Food Safety Knowledge ontology library includes that food is known
Know body and relationship object；At least one pair of food ontologies is associated by described relationship object；Wherein, described relationship object includes
Class relations object, the food in generic food ontologies with father and son's hierarchical relationship is known by described class relations object
Know ontology relation；Non-class relations object is used to be associated between different classes of food ontologies；
Input module, for receiving the query string of client input；
Judge module, is used for judging that described query string is key word, crucial contamination or natural language；
If described query string is key word, then described key word is mated with Food Safety Knowledge ontology library, obtain
Obtain Query Result；
If described query string is crucial contamination, then according to this key contamination determine food ontologies with
The combination of relationship object；
Word-dividing mode, if being natural language for described query string, then carries out participle to described query string, obtains participle
As a result, the combination of food ontologies and relationship object and is determined according to word segmentation result；
Semantic module, for based on described food ontologies and the combination of relationship object, knows according to food safety
Know the food ontologies in ontology library and the combination of relationship object, determine query object, and obtain according to described query object
Query Result；
Return module, for client will be returned to described Query Result.
Alternatively, described after the structure module of structuring food prods security knowledge ontology library, also include:
More new module, operates the renewal of Food Safety Knowledge ontology library for receiving user；Described renewal operation includes:
To the relationship object existed between the food ontologies in described Food Safety Knowledge ontology library and/or food ontologies
Add, revise and delete.
Alternatively, described described query string is carried out participle, obtain word segmentation result, and determine that food is known according to word segmentation result
Know body and the combination of relationship object, including:
Word-dividing mode, for described query string carries out participle, and utilizes concept class dictionary and relation object dictionary to determine point
The part of speech of each participle in word result；Described part of speech includes food ontologies part of speech and relationship object part of speech；
By participle and the participle of relationship object part of speech of food ontologies part of speech, be combined as described food ontologies and
The combination of relationship object.
Alternatively, described based on described food ontologies and the combination of relationship object, according to Food Safety Knowledge body
Food ontologies in storehouse and the combination of relationship object, determine query object, including:
Matching module, for by the participle of the food ontologies in query string and the food in Food Safety Knowledge ontology library
Product ontologies is mated；
First similarity calculation module, if being used for the participle of food ontologies and the food of Food Safety Knowledge ontology library
Product ontologies matches, then the food ontologies on record matching is highest similarity, and calculates this food ontologies
And the first similarity between other food ontologies of Food Safety Knowledge ontology library；
Second similarity calculation module, for for the relationship object associated by each food ontologies, calculate its with
The second similarity between the corresponding corresponding relationship object of food ontologies in query string；
Total similarity calculation module, for by the first similarity of food ontologies be related to this food ontologies
Second similarity of relationship object is multiplied, it is thus achieved that total similarity that food ontologies combines with relationship object；
Select query object module, forward for the total sequencing of similarity selecting food ontologies and relationship object to combine
N number of combination, search its query object.
Alternatively, described based on described food ontologies and the combination of relationship object, according to Food Safety Knowledge body
Food ontologies in storehouse and the combination of relationship object, determine query object, also include:
Expansion module, if being used for the participle of food ontologies and the food ontologies of Food Safety Knowledge ontology library
Do not match, then described word segmentation result is extended, obtain the expanded set of corresponding each food ontologies, described superset
Close and include at least one food ontologies extended；
Matching module, for by the food ontologies of each extension and the food knowledge in Food Safety Knowledge ontology library
Body mates；
First similarity calculation module, if for the food ontologies extended and the food of Food Safety Knowledge ontology library
Product ontologies matches, then the food ontologies on record matching is highest similarity, and calculates this food ontologies
And the first similarity between other food ontologies of Food Safety Knowledge ontology library；
Second similarity calculation module, for for the relationship object associated by each food ontologies, calculate its with
There is the second similarity between the participle of relationship object；
Total similarity calculation module, for by the first similarity of food ontologies be related to this food ontologies
Second similarity of relationship object is multiplied, it is thus achieved that total similarity that food ontologies combines with relationship object；
Select query object module, forward for the total sequencing of similarity selecting food ontologies and relationship object to combine
N number of combination, search its query object.
Alternatively, the described return module that described Query Result is returned to client, including:
Return module, for the combination of N number of food ontologies forward for total sequencing of similarity with relationship object being closed
The information of the another one food ontologies of connection returns to client.
Alternatively, this food ontologies of described calculating and other food ontologies of Food Safety Knowledge ontology library
Between the step of the first similarity, including:
Utilize formula (1)
Calculate first between other food ontologies of this food ontologies and Food Safety Knowledge ontology library
Similarity；Wherein, described t1 is the food ontologies matched, and t2 is that other food of Food Safety Knowledge ontology library is known
Knowing body, n is the hierarchical depth in t1 and t2 hierarchical relationship in Food Safety Knowledge ontology library；δi(t1, t2) it is in level
When the degree of depth is i, the parent relation value between t1 and t2, whereinθiIt is
Weight.
For in first technology, the embodiment of the present invention possesses following advantage:
According in the present invention based on Food Safety Knowledge ontology library, it is proposed that the side of a kind of food safety data information retrieval
Method and system, first structuring food prods security knowledge ontology library, described Food Safety Knowledge ontology library includes food ontologies
And relationship object；At least one pair of food ontologies is associated by described relationship object；Wherein, described relationship object includes that classification is closed
Being object, described class relations object will have the food ontologies of father and son's hierarchical relationship in generic food ontologies
Association；Non-class relations object is used to be associated between different classes of food ontologies；Then looking into according to user's input
Ask string, it is judged that described query string is key word, crucial contamination or natural language, for single key word, by described pass
Keyword mates with Food Safety Knowledge ontology library, it is thus achieved that Query Result；For crucial contamination, then according to this key word
Combination determine the combination of food ontologies and relationship object；For natural language, carry out participle and obtain word segmentation result, root
The combination of food ontologies and relationship object is determined according to word segmentation result；According to the food knowledge in Food Safety Knowledge ontology library
Body and the combination of relationship object, determine query object, and obtain Query Result according to described query object；Finally inquiry is tied
Fruit returns to user.In the Food Safety Knowledge ontology library built, food ontologies has between hierarchical structure, and level logical
Crossing relationship object association, between food ontologies, logic of relation is tight, for the form of the food safety data of user's inquiry
Divide, process respectively for different situations, and word segmentation processing can be carried out for complicated natural language, thus solve
The problem that user cannot accurately find the resource relevant to demand so that user can relatively accurately find and demand
Relevant resource.
Described above is only the general introduction of technical solution of the present invention, in order to better understand the technological means of the present invention,
And can be practiced according to the content of description, and in order to allow above and other objects of the present invention, the feature and advantage can
Become apparent, below especially exemplified by the detailed description of the invention of the present invention.
Accompanying drawing explanation
By reading the detailed description of hereafter preferred implementation, various other advantage and benefit common for this area
Technical staff will be clear from understanding.Accompanying drawing is only used for illustrating the purpose of preferred implementation, and is not considered as the present invention
Restriction.And in whole accompanying drawing, it is denoted by the same reference numerals identical parts.In the accompanying drawings:
Fig. 1 shows the flow chart of steps of the food safety data information retrieval method of the present invention；
Figure 1A shows the system basic functions structure division figure of the present invention；
Figure 1B shows the query string participle flow chart of the present invention；
Fig. 1 C shows the Food Safety Knowledge ontology library part-structure schematic diagram of the present invention；
Fig. 2 shows the structured flowchart of the food safety data information retrieval system of the present invention.
Detailed description of the invention
It is more fully described the exemplary embodiment of the disclosure below with reference to accompanying drawings.Although accompanying drawing shows the disclosure
Exemplary embodiment, it being understood, however, that may be realized in various forms the disclosure and should be by embodiments set forth here
Limited.On the contrary, it is provided that these embodiments are able to be best understood from the disclosure, and can be by the scope of the present disclosure
Complete conveys to those skilled in the art.
Ontologies be relation between field concept and concept standardization describe, this description be specification, clear and definite,
Formal, sharable.The target of ontologies is the knowledge of capture association area, it is provided that the common reason to this domain knowledge
Solve, the vocabulary of common accreditation in determining this field, and be given from the formalization pattern of different levels between these vocabulary and vocabulary
Explicitly defining of mutual relation.
Embodiment one
With reference to Fig. 1, it is shown that according to the side of the food safety data information retrieval of a kind of knowledge based body of the present invention
The flow chart of steps of method embodiment, specifically may include steps of:
Step 100, structuring food prods security knowledge ontology library；Described Food Safety Knowledge ontology library includes food ontologies
And relationship object；At least one pair of food ontologies is associated by described relationship object；Wherein, described relationship object includes that classification is closed
Being object, described class relations object will have the food ontologies of father and son's hierarchical relationship in generic food ontologies
Association；Non-class relations object is used to be associated between different classes of food ontologies；
With reference to Figure 1A, it is shown that the system basic functions structure of the present invention divides figure, including structuring food prods security knowledge originally
Body storehouse, the step of wherein said structuring food prods security knowledge ontology library includes: whole to food ontologies and relationship object thereof
Reason；To food ontologies and the robotic description of relationship object thereof.
Wherein, the food safety data in described Food Safety Knowledge ontology library include: food name, noxious substance, in
Poison event；Collator Mode for food safety data includes: class, attribute, relation.Class be about food name, noxious substance,
The arrangement of the ensemble of all food ontologies of poisoning；Time that attribute such as poisoning occurs, place, generation
Unit, the brief introduction of noxious substance, classification, harm, the production of food, processing, means of transportation etc.；Relation as of equal value, comprise, cause
Deng.
The key data source of structuring food prods security knowledge ontology library includes:
Importing food safety affair from current existing food safety data base, artificial arrangement in food safety affair relates to
And the food ontologies arrived, and analyze the relationship object existed between food ontologies, it is then added to food safety and knows
Know in ontology library；
The food obtaining field of food safety in the various newspaper relevant to food safety, periodical, professional website is utilized to know
Know the relationship object between body and food ontologies, join in Food Safety Knowledge ontology library.
Described Food Safety Knowledge ontology library comprises 3 elements, and { C, R, H}, C represent one group with based food ontologies collection
Close；R represents the set of relation between food ontologies；H represents the food ontologies hierarchical system collection derived from by object
Close.For example:
C={ things, food, food, animal food, vegetable food, dehydrated food, curing food, bakery, tank
Hide food, wholefood, infant food, puffed food, quick frozen food, food additive ... }
R={ processing situation (food, the undressed food of | semi-finished product | of processing food), classification (food, meat | plant |
Complex class | synthetic class), vegetable food classification (food, root | stem | leaf | flower | really | seed | skin | juice), meat food classification
(food, Carnis Sus domestica | beef | Carnis caprae seu ovis | flesh of fish | Carnis Gallus domesticus), and carcinogen (food, nitrous acid category | flavacin | benzopyrene | clenbuterol hydrochloride
| waste oil | formaldehyde) ... }
H={ (things), (things, food), (things, food), (food), (food), (food, food materials), (food is asked
Topic food) ... }
Wherein, Elements C represents with based food ontologies set, it is possible to be referred to as concept set, can be different according to classification
It is divided into food name, noxious substance, poisoning, upper example to be mainly the set of food name class.Element R is food ontologies
Between the set of relationship object, by upper example it can be seen that in bracket be two food ontologies enumerate that (separator represents also
Row relation), the object outside bracket is the relationship object between two food ontologies.Element H is the food derived from by object
Product ontologies hierarchical system set, by upper example it can be seen that " things " can derive " food " and " food " two food
Ontologies, derivative " food " and " food " two food ontologies, as new derivation " parent ", and then can send
The food ontologies of tissue regeneration promoting, such as: " food materials ", " problem food " etc., element H is so that Food Safety Knowledge ontology library is carried out
Expanding, the renewal for Food Safety Knowledge ontology library is significant.
The Food Safety Knowledge ontology library set up describes the semantic relation between food ontologies, food ontologies
Between logic of relation tight, support the reasoning on semantic logic, extensibility is strong.
The various data of field of food safety are arranged, determines between food ontologies and food ontologies
Relationship object, structuring food prods security knowledge ontology library.After described Food Safety Knowledge ontology library builds, use a kind of machine
The readable syntax, such as XML (Extensible Markup Language, can expand markup language), and machine are appreciated that
Resource description framework, such as RDF (Resource Description Framework, resource description framework) is to food safety
Ontologies storehouse is described, serializes to facilitate the storage of information, transmits and process.Wherein, the serializing of XML format represents
It it is the process of form being converted to Obj State to keep or transmit, it is provided that the form of a kind of description scheme data.
Alternatively, after step 100, also include:
Step 105, after the step of described structuring food prods security knowledge ontology library, also includes:
Receive user the renewal of Food Safety Knowledge ontology library is operated；Described renewal operation includes: pacify described food
Omniscient know exist between food ontologies and/or the food ontologies in ontology library the interpolation of relationship object, amendment and
Delete.
With reference to Figure 1A, it is shown that the system basic functions structure of the present invention divides figure, including to Food Safety Knowledge body
The renewal in storehouse: food safety data are arranged, and to the food ontologies in Food Safety Knowledge ontology library and/or pass
It is that object is added, revises and deletes.
Artificially analyze according to the food safety data obtained and deposit between food ontologies and food ontologies
Relationship object, deposit between the food ontologies in described Food Safety Knowledge ontology library and/or food ontologies
Relationship object be updated operation, including the relationship object added between food ontologies and/or food ontologies,
Relationship object between amendment food ontologies and/or food ontologies, deletes food ontologies and/or food knowledge
Relationship object between body.
After described Food Safety Knowledge ontology library builds, user can carry out information retrieval to food safety data.
Step 110, the query string of reception user's input；
With reference to Figure 1A, it is shown that the system basic functions structure of the present invention divides figure, during semantic query, first has to
Receive the query string of user's input.
Step 120, judge described query string be key word, key word combination or natural language；
Wherein, query string three kinds of situations of existence of user's input:
(1) single key word；
(2) combination that multiple key words are constituted；
(3) sentence etc. that natural language is constituted.
Such as, user input " which material causes meat products carcinogenic？" this natural language constitute sentence.
If the described query string of step 130 is key word, then described key word is carried out with Food Safety Knowledge ontology library
Coupling, it is thus achieved that Query Result.
If the described query string of step 140 is crucial contamination, then determine that food is known according to this key contamination
Know body and the combination of relationship object.
If the described query string of step 150 is natural language, then described query string is carried out participle, obtains word segmentation result,
And the combination of food ontologies and relationship object is determined according to word segmentation result；
With reference to Figure 1B, it is shown that the query string participle flow chart of the present invention:
When the query string of user's input is the sentence that natural language is constituted, needs to apply participle, user's input is looked into
Ask string and carry out pretreatment, generate phrase, be converted into first two situation.
Described query string is carried out participle, and utilizes concept class dictionary and relation object dictionary to determine each participle in word segmentation result
Part of speech；Described part of speech includes food ontologies part of speech and relationship object part of speech.
By participle and the participle of relationship object part of speech of food ontologies part of speech, be combined as described food ontologies and
The combination of relationship object.
With user input " which material causes meat products carcinogenic？" this natural language constitute sentence as a example by, to it
Carry out participle, generation phrase: " meat products ", " causing ... carcinogenic ", " which material ", afterwards these phrases be analyzed,
" meat products " is food ontologies, and " causing ... carcinogenic " is relationship object.
Step 160, based on described food ontologies and the combination of relationship object, according in Food Safety Knowledge ontology library
Food ontologies and the combination of relationship object, determine query object, and obtain Query Result according to described query object.
With reference to Figure 1A, it is shown that the system basic functions structure of the present invention divides figure, in semantic query during to count
Calculate similarity, including:
The participle of the food ontologies in query string is entered with the food ontologies in Food Safety Knowledge ontology library
Row coupling；
On the one hand, if the participle of food ontologies mates with the food ontologies of Food Safety Knowledge ontology library
On, then the food ontologies on record matching is highest similarity, and calculates this food ontologies and Food Safety Knowledge
The first similarity between other food ontologies of ontology library；
For the relationship object associated by each food ontologies, calculate its food ontologies corresponding with query string
The second similarity between corresponding relationship object；
The second similarity by the first similarity of food ontologies Yu the relationship object being related to this food ontologies
It is multiplied, it is thus achieved that total similarity that food ontologies combines with relationship object；
Select N number of combination that food ontologies is forward with total sequencing of similarity of relationship object combination, search its inquiry
Object；
And obtain Query Result according to described query object.
On the other hand, if the food ontologies of the participle of food ontologies and Food Safety Knowledge ontology library not
Mix, then described word segmentation result is extended, obtain the expanded set of corresponding each food ontologies, described expanded set bag
Include the food ontologies of at least one extension；
The food ontologies of each extension is mated with the food ontologies in Food Safety Knowledge ontology library；
If the food ontologies of extension matches with the food ontologies of Food Safety Knowledge ontology library, then record
The food ontologies matched is highest similarity, and calculates this food ontologies and Food Safety Knowledge ontology library its
The first similarity between his food ontologies；
For the relationship object associated by each food ontologies, calculate between itself and the participle with relationship object
Second similarity；
The second similarity by the first similarity of food ontologies Yu the relationship object being related to this food ontologies
It is multiplied, it is thus achieved that total similarity that food ontologies combines with relationship object；
Select N number of combination that food ontologies is forward with total sequencing of similarity of relationship object combination, search its inquiry
Object；
And obtain Query Result according to described query object.
If the food ontologies of extension does not matches with the food ontologies of Food Safety Knowledge ontology library, then return
Make the return trip empty value.
In the present invention, similarity analysis method has used for reference calculating and the perception of the semantic distance in linguistics.
Similarity defines: setting t1 and t2 is two food ontologies in Food Safety Knowledge body or relation pair
As, S (t1, t2) represents the similarity degree between the two food ontologies or relationship object, then there is a formula:
Wherein, n is food ontologies or relationship object t1 and t2 food knowledge basis in Food Safety Knowledge ontology library
The depth capacity that body is had.Such as: two food ontologies of t1 and t2 or relationship object are at Food Safety Knowledge body
Storehouse belongs to jth layer and kth layer.Now, and n=max (j, k).θiIt is that weight is (desirable)。δi(t1, t2) value fixed
Justice is as follows:
According to actual needs, can be to the weights θ in above-mentioned formulaiIt is adjusted.
Below, formula is further described.Work as two food ontologies of t1, t2 or relationship object " same
" on, and it belongs to jth layer and kth layer in Food Safety Knowledge ontology library, then min (j, k) individual parent phase before existing
With, 0 ＜ S≤1, when two food ontologies of t1, t2 that and if only if or the relationship object place degree of depth are identical, S=1；Work as t1,
Two food ontologies of t2 or relationship object are on " different ", then without same parent class, then and S=0, represent that similarity degree is
0。
It can be seen that S is in the range of 0～1, when the value of S is bigger, between two food ontologies or relationship object
Similarity degree the biggest.
The Food Safety Knowledge ontology library part-structure schematic diagram of the present invention is shown with reference to Fig. 1 C:
With user input " which material causes meat products carcinogenic？" this natural language constitute sentence as a example by, participle
After obtain " meat products " and " causing ... carcinogenic "；
If Food Safety Knowledge ontology library exists " meat products " " causing ... carcinogenic ", then using similarity formula
Time, the result that similarity is 1 can be obtained, directly determine query object；
If directly existing " meat products " and " causing ... carcinogenic " time different in ontologies storehouse, and " meat products " this food
Product ontologies does not has " carcinogen " this relationship object, when using similarity list to scan for, and the phase of " meat products "
Like in degree list, the similarity of " meat " is strong, and the similarity of " food " is weak；" cause ... carcinogenic " this food ontologies it
Between relationship object, identical with relationship object " carcinogen " similarity in two parts.To sum up, server can select " meat "
" carcinogen " this combination determines query object rather than " food " and " carcinogen " this combination, chooses " meat "
" nitrite " and " clenbuterol hydrochloride " that " carcinogen " this combination is corresponding.
Step 170, described Query Result is returned to client；
With reference to Figure 1A, it is shown that the system basic functions structure of the present invention divides figure, during semantic query, calculate phase
Like information retrieval to be carried out after degree, Query Result is returned to client.
The Food Safety Knowledge ontology library part-structure schematic diagram of the present invention is shown with reference to Fig. 1 C:
With user input " which material causes meat products carcinogenic？" this natural language constitute sentence as a example by, finally
" nitrite " and " clenbuterol hydrochloride " is returned to user.
For in first technology, the embodiment of the present invention possesses following advantage:
According in the present invention based on Food Safety Knowledge ontology library, it is proposed that the side of a kind of food safety data information retrieval
Method, first structuring food prods security knowledge ontology library, described Food Safety Knowledge ontology library includes food ontologies and relation
Object；At least one pair of food ontologies is associated by described relationship object；Wherein, described relationship object includes class relations pair
As, the food ontologies in generic food ontologies with father and son's hierarchical relationship is closed by described class relations object
Connection；Non-class relations object is used to be associated between different classes of food ontologies；Then according to the inquiry of user's input
String, it is judged that described query string is key word, crucial contamination or natural language, for single key word, by described key
Word mates with Food Safety Knowledge ontology library, it is thus achieved that Query Result；For crucial contamination, then according to this key word
Combination determines the combination of food ontologies and relationship object；For natural language, carry out participle and obtain word segmentation result, according to
Word segmentation result determines the combination of food ontologies and relationship object；According to the food knowledge in Food Safety Knowledge ontology library originally
Body and the combination of relationship object, determine query object, and obtain Query Result according to described query object；Finally by Query Result
Return to user.In the Food Safety Knowledge ontology library built, food ontologies has between hierarchical structure, and level and passes through
Relationship object associates, and between food ontologies, logic of relation is tight, and the form for the food safety data of user's inquiry is entered
Row divides, and processes respectively for different situations, and can carry out word segmentation processing for complicated natural language, thus solves use
The problem that family cannot accurately find the resource relevant to demand so that user can relatively accurately find and demand phase
The resource closed.
For embodiment of the method, in order to be briefly described, therefore it is all expressed as a series of combination of actions, but this area
Technical staff should know, the embodiment of the present invention is not limited by described sequence of movement, because implementing according to the present invention
Example, some step can use other orders or carry out simultaneously.Secondly, those skilled in the art also should know, description
Described in embodiment belong to preferred embodiment, necessary to the involved action not necessarily embodiment of the present invention.
Embodiment two
With reference to Fig. 2, it is shown that according to the food safety data information retrieval of a kind of knowledge based body of the present invention be
The structured flowchart of system embodiment, specifically can include such as lower module:
Step 200, builds module, for structuring food prods security knowledge ontology library；Described Food Safety Knowledge ontology library bag
Include food ontologies and relationship object；At least one pair of food ontologies is associated by described relationship object；Wherein, described relation
Object includes class relations object, and described class relations object will have father and son's hierarchical relationship in generic food ontologies
Food ontologies association；Non-class relations object is used to be associated between different classes of food ontologies；
Alternatively, after step 200, also include:
Step 205, more new module, operate the renewal of Food Safety Knowledge ontology library for receiving user；Described renewal
Operation includes: to exist between the food ontologies in described Food Safety Knowledge ontology library and/or food ontologies
The interpolation of relationship object, revise and delete.
After described Food Safety Knowledge ontology library builds, user can carry out information retrieval to food safety data.
Step 210, input module, for receiving the query string of client input；
Step 220, it is judged that module, is used for judging that described query string is key word, crucial contamination or natural language
Speech；
Step 230, Keywords matching module, if being key word for described query string, then by described key word and food
Product security knowledge ontology library mates, it is thus achieved that Query Result；
Step 240, key word combination determines module, if for described query string be crucial contamination time, then basis
This key contamination determines the combination of food ontologies and relationship object；
Step 250, word-dividing mode, if being natural language for described query string, then described query string is carried out participle,
Obtain word segmentation result, and determine the combination of food ontologies and relationship object according to word segmentation result.
Described query string is carried out participle, and utilizes concept class dictionary and relation object dictionary to determine each participle in word segmentation result
Part of speech；Described part of speech includes food ontologies part of speech and relationship object part of speech；
By participle and the participle of relationship object part of speech of food ontologies part of speech, be combined as described food ontologies and
The combination of relationship object.
Step 260, semantic module, based on described food ontologies and the combination of relationship object, pacify according to food
Omniscient knows the food ontologies in ontology library and the combination of relationship object, determines query object, and according to described query object
Obtain Query Result；
On the one hand, if the participle of food ontologies can mate with the food ontologies of Food Safety Knowledge ontology library
Upper:
Matching module, for by the participle of the food ontologies in query string and the food in Food Safety Knowledge ontology library
Product ontologies is mated；
First similarity calculation module, if being used for the participle of food ontologies and the food of Food Safety Knowledge ontology library
Product ontologies matches, then the food ontologies on record matching is highest similarity, and calculates this food ontologies
And the first similarity between other food ontologies of Food Safety Knowledge ontology library；
Second similarity calculation module, for for the relationship object associated by each food ontologies, calculate its with
The second similarity between the corresponding corresponding relationship object of food ontologies in query string；
Total similarity calculation module, for by the first similarity of food ontologies be related to this food ontologies
Second similarity of relationship object is multiplied, it is thus achieved that total similarity that food ontologies combines with relationship object；
Select query object module, forward for the total sequencing of similarity selecting food ontologies and relationship object to combine
N number of combination, search its query object；
Query Result acquisition module, for obtaining Query Result according to described query object.
On the other hand, if the food ontologies of the participle of food ontologies and Food Safety Knowledge ontology library fails
Match:
Expansion module, if being used for the participle of food ontologies and the food ontologies of Food Safety Knowledge ontology library
Do not match, then described word segmentation result is extended, obtain the expanded set of corresponding each food ontologies, described superset
Close and include at least one food ontologies extended；
Matching module, for by the food ontologies of each extension and the food knowledge in Food Safety Knowledge ontology library
Body mates；
First similarity calculation module, if for the food ontologies extended and the food of Food Safety Knowledge ontology library
Product ontologies matches, then the food ontologies on record matching is highest similarity, and calculates this food ontologies
And the first similarity between other food ontologies of Food Safety Knowledge ontology library；
Second similarity calculation module, for for the relationship object associated by each food ontologies, calculate its with
There is the second similarity between the participle of relationship object；
Total similarity calculation module, for by the first similarity of food ontologies be related to this food ontologies
Second similarity of relationship object is multiplied, it is thus achieved that total similarity that food ontologies combines with relationship object；
Select query object module, forward for the total sequencing of similarity selecting food ontologies and relationship object to combine
N number of combination, search its query object；
Query Result acquisition module, for obtaining Query Result according to described query object.
If the food ontologies of extension does not matches with the food ontologies of Food Safety Knowledge ontology library, then return
Make the return trip empty value.
Step 270, returns module, for described Query Result is returned to client.
For in first technology, the embodiment of the present invention possesses following advantage:
According in the present invention based on Food Safety Knowledge ontology library, it is proposed that a kind of food safety data information retrieval be
System, first structuring food prods security knowledge ontology library, described Food Safety Knowledge ontology library includes food ontologies and relation
Object；At least one pair of food ontologies is associated by described relationship object；Wherein, described relationship object includes class relations pair
As, the food ontologies in generic food ontologies with father and son's hierarchical relationship is closed by described class relations object
Connection；Non-class relations object is used to be associated between different classes of food ontologies；Then according to the inquiry of user's input
String, it is judged that described query string is key word, crucial contamination or natural language, for single key word, by described key
Word mates with Food Safety Knowledge ontology library, it is thus achieved that Query Result；For crucial contamination, then according to this key word
Combination determines the combination of food ontologies and relationship object；For natural language, carry out participle and obtain word segmentation result, according to
Word segmentation result determines the combination of food ontologies and relationship object；According to the food knowledge in Food Safety Knowledge ontology library originally
Body and the combination of relationship object, determine query object, and obtain Query Result according to described query object；Finally by Query Result
Return to user.In the Food Safety Knowledge ontology library built, food ontologies has between hierarchical structure, and level and passes through
Relationship object associates, and between food ontologies, logic of relation is tight, and the form for the food safety data of user's inquiry is entered
Row divides, and processes respectively for different situations, and can carry out word segmentation processing for complicated natural language, thus solves use
The problem that family cannot accurately find the resource relevant to demand so that user can relatively accurately find and demand phase
The resource closed.
For system embodiment, due to itself and embodiment of the method basic simlarity, so describe is fairly simple, relevant
Part sees the part of embodiment of the method and illustrates.
Algorithm and display are not intrinsic to any certain computer, virtual system or miscellaneous equipment relevant provided herein.
Various general-purpose systems can also be used together with based on teaching in this.As described above, construct required by this kind of system
Structure be apparent from.Additionally, the present invention is also not for any certain programmed language.It is understood that, it is possible to use various
Programming language realizes the content of invention described herein, and the description done language-specific above is to disclose this
Bright preferred forms.
In description mentioned herein, illustrate a large amount of detail.It is to be appreciated, however, that the enforcement of the present invention
Example can be put into practice in the case of not having these details.In some instances, it is not shown specifically known method, structure
And technology, in order to do not obscure the understanding of this description.
Similarly, it will be appreciated that one or more in order to simplify that the disclosure helping understands in each inventive aspect, exist
Above in the description of the exemplary embodiment of the present invention, each feature of the present invention is grouped together into single enforcement sometimes
In example, figure or descriptions thereof.But, the method for the disclosure should not be construed to reflect an intention that i.e. required guarantor
The application claims feature more more than the feature being expressly recited in each claim protected.More precisely, as following
Claims reflected as, inventive aspect is all features less than single embodiment disclosed above.Therefore,
The claims following detailed description of the invention are thus expressly incorporated in this detailed description of the invention, the most each claim itself
All as the independent embodiment of the present invention.
Those skilled in the art are appreciated that and can carry out the module in the equipment in embodiment adaptively
Change and they are arranged in one or more equipment different from this embodiment.Can be the module in embodiment or list
Unit or assembly are combined into a module or unit or assembly, and can put them in addition multiple submodule or subelement or
Sub-component.In addition at least some in such feature and/or process or unit excludes each other, can use any
Combine all features disclosed in this specification (including adjoint claim, summary and accompanying drawing) and so disclosed appoint
Where method or all processes of equipment or unit are combined.Unless expressly stated otherwise, this specification (includes adjoint power
Profit requires, summary and accompanying drawing) disclosed in each feature can be carried out generation by providing identical, equivalent or the alternative features of similar purpose
Replace.
Although additionally, it will be appreciated by those of skill in the art that embodiments more described herein include other embodiments
Some feature included by rather than further feature, but the combination of the feature of different embodiment means to be in the present invention's
Within the scope of and form different embodiments.Such as, in the following claims, embodiment required for protection appoint
One of meaning can mode use in any combination.
The all parts embodiment of the present invention can realize with hardware, or to run on one or more processor
Software module realize, or with combinations thereof realize.It will be understood by those of skill in the art that and can use in practice
Microprocessor or digital signal processor (DSP) realize the food safety of knowledge based body according to embodiments of the present invention
The some or all functions of the some or all parts in the method and system equipment of data information retrieval.The present invention also may be used
To be embodied as part or all the equipment for performing method as described herein or (such as, the calculating of device program
Machine program and computer program).The program of such present invention of realization can store on a computer-readable medium, or
Can be to have the form of one or more signal.Such signal can be downloaded from internet website and obtain, or carrying
There is provided on body signal, or provide with any other form.
The present invention will be described rather than limits the invention to it should be noted above-described embodiment, and ability
Field technique personnel can design alternative embodiment without departing from the scope of the appended claims.In the claims,
Any reference marks that should not will be located between bracket is configured to limitations on claims.Word " comprises " and does not excludes the presence of not
Arrange element in the claims or step.Word "a" or "an" before being positioned at element does not excludes the presence of multiple such
Element.The present invention and can come real by means of including the hardware of some different elements by means of properly programmed computer
Existing.If in the unit claim listing equipment for drying, several in these devices can be by same hardware branch
Specifically embody.Word first, second and third use do not indicate that any order.These word explanations can be run after fame
Claim.
Claims (10)
1. the method for the food safety data information retrieval of a knowledge based body, it is characterised in that including:
Structuring food prods security knowledge ontology library；Described Food Safety Knowledge ontology library includes food ontologies and relationship object；
At least one pair of food ontologies is associated by described relationship object；Wherein, described relationship object includes class relations object, described
The food ontologies in generic food ontologies with father and son's hierarchical relationship is associated by class relations object；Inhomogeneity
Non-class relations object is used to be associated between other food ontologies；
Receive the query string of client input；
Judge that described query string is key word, key word combination or natural language；
If described query string is key word, then described key word is mated with Food Safety Knowledge ontology library, it is thus achieved that look into
Ask result；
If described query string is crucial contamination, then determine food ontologies and relation according to this key contamination
The combination of object；
If described query string is natural language, then described query string is carried out participle, obtain word segmentation result, and tie according to participle
Fruit determines the combination of food ontologies and relationship object；
Based on described food ontologies and the combination of relationship object, according to the food knowledge in Food Safety Knowledge ontology library originally
Body and the combination of relationship object, determine query object, and obtain Query Result according to described query object；
Described Query Result is returned to client.
2. the method for claim 1, it is characterised in that after the step of described structuring food prods security knowledge ontology library,
Also include:
Receive user the renewal of Food Safety Knowledge ontology library is operated；Described renewal operation includes: know described food safety
Know the interpolation of the relationship object existed between food ontologies and/or food ontologies in ontology library, revise and delete.
Method the most according to claim 1, it is characterised in that described described query string is carried out participle, obtains participle knot
Really, and determine the combination of food ontologies and relationship object according to word segmentation result, including:
Described query string is carried out participle, and utilizes concept class dictionary and relation object dictionary to determine the word of each participle in word segmentation result
Property；Described part of speech includes food ontologies part of speech and relationship object part of speech；
By participle and the participle of relationship object part of speech of food ontologies part of speech, it is combined as described food ontologies and relation
The combination of object.
Method the most according to claim 1, it is characterised in that described based on described food ontologies and relationship object
Combination, according to the food ontologies in Food Safety Knowledge ontology library and the combination of relationship object, determines query object, bag
Include:
Food ontologies in the participle of the food ontologies in query string and Food Safety Knowledge ontology library is carried out
Join；
If the participle of food ontologies matches with the food ontologies of Food Safety Knowledge ontology library, then record matching
On food ontologies be highest similarity, and calculate this food ontologies and Food Safety Knowledge ontology library other
The first similarity between food ontologies；
For the relationship object associated by each food ontologies, calculate its food ontologies corresponding to query string corresponding
Relationship object between the second similarity；
First similarity of food ontologies is multiplied with the second similarity of the relationship object being related to this food ontologies,
Obtain total similarity of food ontologies and relationship object combination；
Select N number of combination that food ontologies is forward with total sequencing of similarity of relationship object combination, search its query object.
Method the most according to claim 4, it is characterised in that described based on described food ontologies and relationship object
Combination, according to the food ontologies in Food Safety Knowledge ontology library and the combination of relationship object, determines query object, also wraps
Include:
If the participle of food ontologies does not matches with the food ontologies of Food Safety Knowledge ontology library, then to described
Word segmentation result is extended, and obtains the expanded set of corresponding each food ontologies, and described expanded set includes that at least one expands
The food ontologies of exhibition；
The food ontologies of each extension is mated with the food ontologies in Food Safety Knowledge ontology library；
If the food ontologies of extension matches with the food ontologies of Food Safety Knowledge ontology library, then record matching
On food ontologies be highest similarity, and calculate this food ontologies and Food Safety Knowledge ontology library other
The first similarity between food ontologies；
For the relationship object associated by each food ontologies, calculate second between itself and the participle with relationship object
Similarity；
First similarity of food ontologies is multiplied with the second similarity of the relationship object being related to this food ontologies,
Obtain total similarity of food ontologies and relationship object combination；
Select N number of combination that food ontologies is forward with total sequencing of similarity of relationship object combination, search its query object.
Method the most according to claim 1, it is characterised in that the described step that described Query Result is returned to client
Suddenly, including:
N number of food ontologies forward for total sequencing of similarity is known with the another one food associated by the combination of relationship object
The information knowing body returns to client.
7. method as claimed in claim 4, it is characterised in that this food ontologies of described calculating is with Food Safety Knowledge originally
The step of the first similarity between other the food ontologies in body storehouse, including:
Utilize formula (1)
Calculate first between this food ontologies and other food ontologies of Food Safety Knowledge ontology library similar
Degree；Wherein, described t1 is the food ontologies matched, and t2 is the food knowledge basis of other of Food Safety Knowledge ontology library
Body, n is the hierarchical depth in t1 and t2 hierarchical relationship in Food Safety Knowledge ontology library；δi(t1, t2) it is in hierarchical depth
During for i, the parent relation value between t1 and t2, whereinθiIt it is weight.
8. the system of the food safety data information retrieval of a knowledge based body, it is characterised in that including:
Build module, for structuring food prods security knowledge ontology library；Described Food Safety Knowledge ontology library includes that food knowledge is originally
Body and relationship object；At least one pair of food ontologies is associated by described relationship object；Wherein, described relationship object includes classification
Relationship object, described class relations object will have the food knowledge of father and son's hierarchical relationship originally in generic food ontologies
Body associates；Non-class relations object is used to be associated between different classes of food ontologies；
Input module, for receiving the query string of client input；
Judge module, is used for judging that described query string is key word, crucial contamination or natural language；
If described query string is key word, then described key word is mated with Food Safety Knowledge ontology library, it is thus achieved that look into
Ask result；
If described query string is crucial contamination, then determine food ontologies and relation according to this key contamination
The combination of object；
Word-dividing mode, if being natural language for described query string, then carries out participle to described query string, obtains participle knot
Really, the combination of food ontologies and relationship object and is determined according to word segmentation result；
Semantic module, is used for based on described food ontologies and the combination of relationship object, according to Food Safety Knowledge originally
Food ontologies in body storehouse and the combination of relationship object, determine query object, and obtain inquiry according to described query object
Result；
Return module, for client will be returned to described Query Result.
9. system as claimed in claim 8, it is characterised in that the described structure mould for structuring food prods security knowledge ontology library
After block, also include:
More new module, operates the renewal of Food Safety Knowledge ontology library for receiving user；Described renewal operation includes: to institute
State the adding of relationship object existed between the food ontologies in Food Safety Knowledge ontology library and/or food ontologies
Add, revise and delete.
System the most according to claim 8, it is characterised in that described described query string is carried out participle, obtains participle knot
Really, and determine the combination of food ontologies and relationship object according to word segmentation result, including:
Word-dividing mode, for described query string carries out participle, and utilizes concept class dictionary and relation object dictionary to determine that participle is tied
The part of speech of each participle in Guo；Described part of speech includes food ontologies part of speech and relationship object part of speech；
By participle and the participle of relationship object part of speech of food ontologies part of speech, it is combined as described food ontologies and relation
The combination of object.
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