CN103177124A - Dielectric constant database searching method and dielectric constant database searching system - Google Patents
Dielectric constant database searching method and dielectric constant database searching system Download PDFInfo
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- 229910052500 inorganic mineral Inorganic materials 0.000 claims description 122
- 239000011707 mineral Substances 0.000 claims description 122
- 150000001875 compounds Chemical class 0.000 claims description 61
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- 229910052751 metal Inorganic materials 0.000 claims description 35
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- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 36
- YDZQQRWRVYGNER-UHFFFAOYSA-N iron;titanium;trihydrate Chemical compound O.O.O.[Ti].[Fe] YDZQQRWRVYGNER-UHFFFAOYSA-N 0.000 description 19
- 239000010936 titanium Substances 0.000 description 17
- 229910052719 titanium Inorganic materials 0.000 description 17
- RTAQQCXQSZGOHL-UHFFFAOYSA-N Titanium Chemical compound [Ti] RTAQQCXQSZGOHL-UHFFFAOYSA-N 0.000 description 16
- 229910052742 iron Inorganic materials 0.000 description 16
- NIFIFKQPDTWWGU-UHFFFAOYSA-N pyrite Chemical compound [Fe+2].[S-][S-] NIFIFKQPDTWWGU-UHFFFAOYSA-N 0.000 description 16
- 229910052683 pyrite Inorganic materials 0.000 description 9
- 239000011028 pyrite Substances 0.000 description 9
- GWEVSGVZZGPLCZ-UHFFFAOYSA-N Titan oxide Chemical compound O=[Ti]=O GWEVSGVZZGPLCZ-UHFFFAOYSA-N 0.000 description 8
- 229910052960 marcasite Inorganic materials 0.000 description 7
- 239000012141 concentrate Substances 0.000 description 6
- JYGXADMDTFJGBT-VWUMJDOOSA-N hydrocortisone Chemical compound O=C1CC[C@]2(C)[C@H]3[C@@H](O)C[C@](C)([C@@](CC4)(O)C(=O)CO)[C@@H]4[C@@H]3CCC2=C1 JYGXADMDTFJGBT-VWUMJDOOSA-N 0.000 description 6
- MBMLMWLHJBBADN-UHFFFAOYSA-N Ferrous sulfide Chemical compound [Fe]=S MBMLMWLHJBBADN-UHFFFAOYSA-N 0.000 description 5
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- CWYNVVGOOAEACU-UHFFFAOYSA-N Fe2+ Chemical compound [Fe+2] CWYNVVGOOAEACU-UHFFFAOYSA-N 0.000 description 3
- PWHULOQIROXLJO-UHFFFAOYSA-N Manganese Chemical compound [Mn] PWHULOQIROXLJO-UHFFFAOYSA-N 0.000 description 3
- DQMUQFUTDWISTM-UHFFFAOYSA-N O.[O-2].[Fe+2].[Fe+2].[O-2] Chemical compound O.[O-2].[Fe+2].[Fe+2].[O-2] DQMUQFUTDWISTM-UHFFFAOYSA-N 0.000 description 3
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- 229910052748 manganese Inorganic materials 0.000 description 3
- 239000011572 manganese Substances 0.000 description 3
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- 229910005451 FeTiO3 Inorganic materials 0.000 description 1
- NINIDFKCEFEMDL-UHFFFAOYSA-N Sulfur Chemical compound [S] NINIDFKCEFEMDL-UHFFFAOYSA-N 0.000 description 1
- 239000005864 Sulphur Substances 0.000 description 1
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Abstract
The invention provides a dielectric constant database searching method and a dielectric constant database searching system. The dielectric constant database searching method comprises the following steps of: (A) establishing a concept tree; (B) searching user search words in the concept tree so as to obtain more related search words; (C) generating a query condition expression formula; (D) searching a database; and (E) reordering searched results. The invention also provides the dielectric constant database searching system which comprises the database, a database management module, a concept tree generating module, an interface inputting module, an SQL (Structured Query Language) statement generating module, a database searching module and an interface displaying module. The dielectric constant database searching method and the dielectric constant database searching system have the advantages of improving the relevance of information research of a relational database, and saving the information searching time of users; further quantizing the relevance in combination of the concept tree, introducing relevance parameters, and providing more options between accuracy and ambiguity when the users research information; and further dynamically calculating weight numbers by using the relation between the search words and the concept and further promoting user experience.
Description
Technical field
The present invention relates to the database retrieval field, relate in particular to a kind of specific inductive capacity database index method and system.
Background technology
The specific inductive capacity of mineral has important reference value at many scientific research fields, and specific inductive capacity refers to that material keeps the ability of electric charge, claims again permittivity or relative permittivity, characterizes a significant data of dielectric or insulating material electrical property.In field of metallurgy, the related mineral of mineral specific inductive capacity database record is very many, and the information that how according to user's term, effectively retrieves the user and need in the databases of a large amount of records is also an important research direction of various professional domain Database Systems.
While usually in database, retrieving the mineral specific inductive capacity, can be retrieved according to the title of mineral.As retrieval " troilite ", adopt conventional database index method, can apply SQL(Structured Query Language) statement carrys out the value that the value of certain field (Field) in the table (Table) of searching database is a certain appointment, for example: " SELECT mineral name, specific inductive capacity FROM mineral specific inductive capacity table WHERE mineral name=' ilmenite ' " such statement carrys out searching database.This retrieval mode often retrieves single information, and can't obtain the mineral that are associated with " ilmenite ", as the specific inductive capacity information of " ferrous manganese ore ", " troilite ".Under this mode, the user often needs repeatedly to input term just can retrieve needed information, and each demonstration result is all single, and the information that some users can not be needed be integrated together demonstration, so that user's comparative study.At present a lot of searching systems are by the advanced search mode is provided, and input a plurality of terms by the user and realize with the structure retrieve statement, and this mode also needs the more term of user's typing, very inconvenient user's use.
In order to obtain more information, to single term, common way is exactly to change the conditional expression of SQL statement into the fuzzy search mode, and term is split, as: can split into conditional expression " mineral name LIKE ' % sulphur % ' ", " mineral name LIKE ' % iron % ' " and " mineral name LIKE ' % ore deposit % ' " to " troilite ", then these conditional expressions are configured to retrieve statement and are retrieved in database, finally result for retrieval is combined by the UNION conjunction.This retrieval mode will retrieve again a large amount of and the incoherent information of the expectation user, and the user requires a great deal of time from row filter and judgement, that is to say, quantity of information is very large, but the degree of correlation is very low.Another kind method is exactly to resolve term by the rule of certain technical term, as " troilite " resolved to " troilite " and " iron ore ", and " ferrous manganese ore " is resolved to " ferrous manganese ore " and " iron ore ", and then carries out fuzzy search.But a lot of technical terms do not have unified rule and can follow, as " ilmenite concentrate ", if resolve to " ilmenite concentrate " and " concentrate " is obviously improper.Simultaneously, use the fuzzy search mode, Database Systems will the scan text field when retrieval, if the excessive use fuzzy search will cause the retrieval performance of system to descend.
Summary of the invention
For the problems referred to above, the invention provides a kind of specific inductive capacity database index method, comprise the steps:
(A) set up conceptional tree: between the concept in the affiliated field of utilization, certain inherent relation factor is set up conceptional tree, described conceptional tree is divided into multilayer, ground floor is root node, except root node, each node in conceptional tree at least comprises value and the weights of search field in one or more database table;
(B) search subscriber term in conceptional tree, to obtain more heterogeneous pass term: after the term that obtains user's input, in described conceptional tree according to the value of certain decision search search field, if exist the value of this node search field and term to be complementary, by rule, this node and junction associated thereof are inserted in a node list, after completing search, return to this node list;
(C) generated query conditional expression: if the node list of returning is not for empty, order travels through the node in the node list, the field that the value of search field and term are complementary forms expression formula by " field name=field value ", between a plurality of expression formulas, with logical connective " OR ", is connected.After complete node list of traversal, generate a complete SQL query conditional expression, carry out next step (D), if the node list of returning is returned to empty final result for retrieval for empty;
(D) searching database: the querying condition expression formula according to generating, further generate complete SQL query statement, submit to database and retrieved and return results collection;
(E) result for retrieval rearrangement: result set is re-started to sequence by the weights of node in the node list in internal memory, and return to final result for retrieval, empty the node list.
In step (B), if conceptional tree is the n layer, for improving the degree of correlation of retrieving information, described search strategy is: first search for the n layer, first search for leaf node, if searched for the n layer, the value of search field and the node that term is complementary are arranged, insert the node list by rule, and return to the node list, finish search; If do not search, continue search n-1 layer, by that analogy, until search the root node of the 1st layer, show to search for unsuccessfully, return to empty node list.
In step (B), for quantizing the degree of correlation, according to the number of plies of conceptional tree, introduce degree of correlation parameter, the node that insertion searches in described node list and the rule of junction associated thereof decide by degree of correlation parameter:
Degree of correlation parameter r, the number of plies of conceptional tree is n, the span of degree of correlation parameter r is: 1<r≤n, when at the i layer, searching node, its degree of correlation parameter r >=i,, by this node and the described node list of descendants's Knots inserting thereof, to leaf node, only insert this leaf node in described node list; If r<i, by this node in the described node list of all descendants's Knots insertings of the father node of i layer and father node thereof.
In step (A), described conceptional tree further is configured to: ground floor is root node, the second layer is metallic element, the 3rd layer is compound, the 4th layer is mineral, the child node of metallic element node is the compound containing this metallic element, the child node of compound node is the mineral containing this compound, except root node, the information of each node is except the field value that comprises mineral name, also comprise molecular formula, grade and weights, the content of the compound of contained its father node of mineral that the grade of mineral node is this node, for number percent, the grade of all the other nodes all is set to 1.
In step (B), the weights of the node of described conceptional tree are after searching node at every turn, dynamic calculation while inserting the node list, the weights of node calculate like this: when the grade of the node be retrieved is P, its weights W, need to improve weights, W=P+1; And, to its child node, sibling or father node, need to reduce weights, when the grade of a certain node is P
i, the weights that this node is corresponding are W
i=P
i* P.
The present invention also provides a kind of specific inductive capacity database retrieval system, and this system comprises:
Database, at least comprise mineral specific inductive capacity table and mineral composition table;
Database management module, for the record of the various tables of maintenance data base;
The conceptional tree generation module, set for the automatic product concept of internal memory that is recorded in from existing database;
The interface load module, for inputting interface being provided to the user and obtaining the term of user's input, send term to the SQL statement generation module;
The SQL statement generation module, the term imported into for the reception interface load module, and, under the guidance of conceptional tree, obtain complete SQL query statement, send the SQL query statement to the database retrieval module;
The database retrieval module, for mutual with Database Systems, submit complete SQL statement to Database Systems, and the retrieval set that Database Systems are returned in internal memory by weights rearrangements, send the final result for retrieval after sequence to interface display module;
Interface display module, by final result for retrieval to user-friendly demonstration.
Described conceptional tree generation module further comprises: the metallic element administration module, for safeguarding the metallic element list; Compound and mineral information extraction modules, for extracting database compound and mineral information list.
When product concept is set, at first the conceptional tree generation module generates root node; The metallic element list provided according to the metallic element administration module again generates the metallic element node of the second layer; Next, the compound and the mineral information list that utilize compound and mineral information extraction modules to provide, generate the compound node of the 3rd layer according to the metallic element that whether comprises the second layer in compound; Finally, according to the compound that whether comprises the 3rd layer in compound and mineral information list, generate the compound node of the 4th layer, and then complete the generation of whole conceptional tree.
Described SQL statement generation module further comprises: the conceptional tree search module, and for the search concept tree, search the docuterm segment value that coupling is arranged with term, and the node of coupling and junction associated thereof are inserted in the node list; SQL query expression formula generation module, utilize the node in the node list to generate the SQL query expression formula; SQL statement load module, generate complete SQL statement and send the database retrieval module to according to the SQL query expression formula.
The database retrieval module further comprises: the database interactive module, and for mutual with Database Systems, the connection data storehouse is also submitted the SQL query statement to Database Systems, receives the retrieval set that Database Systems are passed back; The result set order module, for the retrieval set that the database interactive module is returned, the weights rearrangement in conjunction with node in the node list, send the result after sequence to interface display module, and empty the node list.
The invention has the beneficial effects as follows:
1) basic ideas of the present invention are to utilize certain the inherent incidence relation between field concept to set up conceptional tree, the user search word is used to the conceptional tree guidance, obtain the term more be associated with the user search word, utilize " OR " logical connective formation condition expression formula, and then the correlativity of raising traditional relational database retrieval, practical application shows, the present invention has significantly improved the degree of correlation of traditional relational information retrieval, saved the time that the user searches information;
2) in conjunction with conceptional tree, further quantize the degree of correlation, introduce degree of correlation parameter, during for user search information, accurately and between fuzzy providing more option, be more convenient for user's use;
3) utilize and concern the dynamic calculation weights between term and concept, the recycling Dynamic Weights re-starts sequence, makes better " perception " user of system, further promotes user's experience;
4) whole retrieval only completes in the wall scroll query statement, and do not comprise any subquery, when being convenient to Database Systems and carrying out query optimization, also effectively reduced with the mutual of Database Systems and reduced the burden of Database Systems, having improved the execution efficiency of whole system;
When 5) improving the degree of correlation of retrieving information, avoid use Like operational character, improved the retrieval rate of Database Systems.
the accompanying drawing explanation:
Fig. 1 is the main process flow diagram of a kind of specific inductive capacity database index method of the present invention;
Fig. 2 is the structured flowchart of a kind of specific inductive capacity database retrieval system of the present invention;
Fig. 3 is the schematic diagram of the mineral conceptional tree of embodiments of the invention.
embodiment:
In order to make the technician clearer to purpose of the present invention, advantage, below in conjunction with accompanying drawing, the present invention will be further described.
embodiment 1:
As shown in Figure 1, be the main flow process of the method for the invention.The method comprises:
Step S101: set up conceptional tree, between the concept in the affiliated field of utilization, the internal association factor is set up conceptional tree, described conceptional tree is divided into multilayer, ground floor is root node, except root node, each node in conceptional tree at least comprises the value of the field be retrieved in weights and one or more database table;
Conceptional tree is configured to: ground floor is root node, the second layer is metallic element, the 3rd layer is compound, the 4th layer is mineral, the child node of metallic element node is the compound containing this metallic element, the child node of compound node is the mineral containing this compound, except root node, the information of each node is except the field value that comprises mineral name, also comprise molecular formula, grade and weights, the content of the compound of contained its father node of mineral that the grade of mineral node is this node, be number percent, and the grade of all the other nodes all is set to 1.
Step S102: the term that search is associated with the user search word in conceptional tree, after the term that obtains user's input, search field value in described conceptional tree, if exist the field value of this node and term to be complementary, by rule, this node and junction associated thereof are inserted in a node list, continue to carry out search, until search for complete conceptional tree, and return to the node list;
If described conceptional tree is the n layer, for improving the degree of correlation of retrieving information, described search strategy is: first search for the n layer, first search for leaf node, if searched for the n layer, the value of search field and the node that term is complementary are arranged, insert the node list by rule, and return to the node list, finish search; If do not search, continue search n-1 layer, by that analogy, until search the root node of the 1st layer, show to search for unsuccessfully, return to empty node list.
For quantizing the degree of correlation, according to the number of plies of conceptional tree, introduce degree of correlation parameter, the node that insertion searches in described node list and the rule of junction associated thereof decide by degree of correlation parameter:
Degree of correlation parameter r, the number of plies of conceptional tree is n, the span of degree of correlation parameter r is: 1<r≤n, when at the i layer, searching node, its degree of correlation parameter r >=i,, by this node and the described node list of descendants's Knots inserting thereof, to leaf node, only insert this leaf node in described node list; If r<i, by this node in the described node list of all descendants's Knots insertings of the father node of i layer and father node thereof.
The weights of the node of conceptional tree are after searching node at every turn, dynamic calculation while inserting the node list, and the weights of node calculate like this: when the grade of the node be retrieved is P, its weights W, need to improve weights, W=P+1; And, to its child node, sibling or father node, need to reduce weights, when the grade of a certain node is P
i, the weights that this node is corresponding are W
i=P
i* P.
Step S103: generated query conditional expression, if the node list of returning is not for empty, order travels through the node in the node list, field value coupling term field value in node is pressed: " field name=field value ", generate expression formula, connected with logical connective " OR " between a plurality of expression formulas.After complete node list of traversal, generate a complete SQL query conditional expression, carry out next step S104, if the node list of returning is returned to empty final result for retrieval for empty;
Step S104: searching database, the querying condition expression formula according to generating, further generate complete SQL query statement, submits to database and retrieved and return results collection;
Step S105: the result for retrieval rearrangement, result set is re-started to sequence by the weights of node in the node list in internal memory, and return to final result for retrieval, empty the node list.
As shown in Figure 2, be the structured flowchart of a kind of specific inductive capacity database retrieval system of the present invention, this system comprises:
Database, at least comprise mineral specific inductive capacity table and mineral composition table;
Conceptional tree generation module 202, set for the automatic product concept of internal memory that is recorded in from existing database;
Interface load module 203, for inputting interface being provided to the user and obtaining the term of user's input, send term to the SQL statement generation module;
SQL statement generation module 204, the term imported into for the reception interface load module, and, under the guidance of conceptional tree, obtain complete SQL query statement, send the SQL query statement to the database retrieval module;
Described conceptional tree generation module 202 further comprises: the metallic element administration module, for safeguarding the metallic element list; Compound and mineral information extraction modules, for extracting database compound and mineral information list.When product concept is set, at first conceptional tree generation module 202 generates root node; The metallic element list provided according to the metallic element administration module again generates the metallic element node of the second layer; Next, the compound and the mineral information list that utilize compound and mineral information extraction modules to provide, generate the compound node of the 3rd layer according to the metallic element that whether comprises the second layer in compound; Finally, according to the compound that whether comprises the 3rd layer in compound and mineral information list, generate the compound node of the 4th layer, and then complete the generation of whole conceptional tree.
Described SQL statement generation module 204 further comprises: the conceptional tree search module, and for the search concept tree, search the docuterm segment value that coupling is arranged with term, and the node of coupling and junction associated thereof are inserted in the node list; SQL query expression formula generation module, utilize the node in the node list to generate the SQL query expression formula; SQL statement load module, generate complete SQL statement and send database retrieval module 205 to according to the SQL query expression formula.
Below in conjunction with instantiation, the angle from exploitation and application, elaborate to the present invention again.
embodiment 2:
As shown in table 1, be the mineral specific inductive capacity table in the database of the present embodiment, mainly comprise: the fields such as ID, mineral name, specific inductive capacity, dielectric loss and grade, ID is major key.Table 2 is the mineral composition table, comprising: the fields such as ID, compound, Chinese name, number percent, grade mark, wherein, the major key of combining that ID is the mineralogical composition table with compound.The ID of mineral composition table is the external key of mineral specific inductive capacity table.
Table 1
Table 2
The foundation of conceptional tree can be edited foundation by related software, also can automatically set up by program mode (PM), conceptional tree generation module 202 is recorded in notional certain internal association factor and can further sets up conceptional tree according to the field be retrieved, in field of metallurgy, a main relation factor between mineral is exactly chemical element, compound and mineral composition, in the present embodiment, name adopts " mineral name " as search field, and has adopted a kind of method of automatically setting up conceptional tree at conceptional tree generation module 202:
A) set up the metallic element list;
B) from mineral composition table and mineral specific inductive capacity table, by correlation inquiry, obtain compound and mineral list;
C) further, first set up the root node of conceptional tree;
D) generate second layer metal element node by the metallic element table, the value of its search field " mineral name " is: the metallic element Chinese names such as iron, titanium, and corresponding molecular formula is Fe, Ti, and grade all is set to 1, and the weights acquiescence is made as 1;
E) according to compound and mineral list, judge the metallic element that whether comprises the second layer in compound, further generate the compound node of the 3rd layer, as: di-iron trioxide Fe
2o
3in, contain iron Fe, di-iron trioxide Fe
2o
3for its child node, the value of its search field " mineral name " is: the Chinese name of the compounds such as di-iron trioxide, tri-iron tetroxide, corresponding molecular formula is Fe
2o
3, Fe
3o
4deng, grade all is set to 1, and the weights acquiescence is made as 1;
F), according to compound and mineral list, judge whether the compound of the 3rd layer comprises mineral, and then obtain the mineral node of the 4th layer, as contained compound F 17-hydroxy-corticosterone e in magnetic iron ore
3o
4, magnetic iron ore is tri-iron tetroxide Fe
3o
4child node, the value of its search field " mineral name " is: the Chinese name of mineral such as " magnetic iron ore ", the molecular formula Fe that corresponding molecular formula is its main compound
3o
4, grade is its contained compound F 17-hydroxy-corticosterone e
3o
4content 56%, weights acquiescences is made as 1;
Through above process, can obtain mineral conceptional tree as shown in Figure 3.
In practical application, degree of correlation parameter r can be set to 3.The user is by interface load module 203 input terms, as " pyrite ", at first conceptional tree search module in SQL statement generation module 204 searches for the mineral node at the 4th layer of conceptional tree, when the value that searches search field " mineral name " is the node of " pyrite ", degree of correlation parameter r is set to 3, and the number of plies i of the node retrieved is 4, meet r<i, this node and sibling thereof and father node are calculated weights and insert in the node list, until searched for all nodes of the 4th layer, three nodes are arranged in now node list, respectively " pyrite " " marcasite " and " ferrous disulfide ", finish search.
Next step is exactly according to node list generated query conditional expression, and three node of the SQL query expression formula generation module in SQL statement generation module 204 in above-mentioned node list and search field name " mineral name " further generated query conditional expression are: " mineral name=' pyrite ' OR mineral name=' marcasite ' OR mineral name=' ferrous disulfide ' ".
Next the SELEC statement that SQL statement load module will be set in advance: " SELECT mineral name, grade, specific inductive capacity, dielectric loss FROM mineral specific inductive capacity table " and query expression assemble up, and generate complete query expression:
" SELECT mineral name, grade, specific inductive capacity, dielectric loss FROM mineral specific inductive capacity table WHERE mineral name=' pyrite ' OR mineral name=' marcasite ' OR mineral name=' ferrous disulfide ' "
This SQL statement is submitted to database retrieval module 205 and is retrieved in database.When the user inputs term for " pyrite ", SQL statement generation module 204 when inserting node in the node list, calculate weights according to the weights computation rule, " pyrite " weights are 1+0.422=1.422, " marcasite " weights are 0.422*0.412=0.174, retrieval through database retrieval module 205, obtained retrieval set, to retrieval set, according to weights, by descending sort, also final result for retrieval is passed to interface display module 206 shows the user to order module in database retrieval module 205, obtain result for retrieval as shown in table 3:
Table 3
When the user inputs term for " marcasite ", " marcasite " weights are 1+0.412=1.412, " pyrite " weights are 0.422*0.412=0.174, order module in database retrieval module 205 is pressed descending sort to retrieval set according to weights, obtains the result for retrieval shown in table 4:
Table 4
That is to say, system has realized carrying out dynamic order according to user's term, makes better " perception " user of system, has further promoted user's experience.
embodiment 3:
In practical application, " ilmenite " be iron content both, also titaniferous, and therefore, many places have appearred in ilmenite in conceptional tree, and for example in most " dauphinite ", also contain certain FeTiO
3, in the present embodiment, " dauphinite " also is included into compound F 17-hydroxy-corticosterone eTiO
3child node, " dauphinite " just.When the user inputs terms " ilmenite " from interface load module 203, degree of correlation parameter is set to r=3,204 the 4th layer of search mineral nodes at conceptional tree of SQL statement generation module, until searched for all mineral nodes, to obtain two places " ilmenite ", when inserting the node list, mineral of the same name only insert a node, and the last query statement generated is:
" SELECT mineral name, grade, specific inductive capacity, dielectric loss FROM mineral specific inductive capacity table WHERE mineral name=' ilmenite ' OR mineral name=' dauphinite ' OR mineral name=' FeTiO
3' ".
SQL statement generation module 204 is submitted to database retrieval module 205 by this SQL statement and is retrieved in database, by retrieval, can obtain the information of the specific inductive capacity of " ilmenite " and associated " dauphinite ", result for retrieval is showed to the user by interface display module 206.
If degree of correlation parameter is set to r=2, meet r<i, in conceptional tree as shown in Figure 3, the father node of the 2nd layer of " ilmenite " has " titanium " and " iron ", by rule, conceptional tree search module in SQL statement generation module 204 will comprise that compound node and mineral node all insert in the node list to all child nodes of " titanium " and " iron ", and the SQL statement finally generated is:
" SELECT mineral name, grade, specific inductive capacity, dielectric loss FROM mineral specific inductive capacity table WHERE mineral name=' titanium ' OR mineral name=' titania ' OR mineral name=' FeTiO
3' OR mineral name=' ilmenite ' OR mineral name=' dauphinite ' OR mineral name=' high titanium slag ' OR mineral name=' ilmenite concentrate ' OR mineral name=' iron ' OR " mineral name=' pyrite ' OR mineral name=' marcasite ' OR mineral name=' ferrous disulfide ' ... ".
Its result for retrieval comprises all mineral of " titanium " and " iron ", that is to say, has reduced the degree of correlation, and the retrieving information obfuscation has also obtained more retrieving information.
If degree of correlation parameter is set to r=4, meet r >=i, and be leaf node, the SQL statement generated is:
" SELECT mineral name, grade, specific inductive capacity, dielectric loss FROM mineral specific inductive capacity table WHERE mineral name=' ilmenite ' ".
Its result for retrieval only obtains the retrieving information of " ilmenite ", has improved the degree of correlation, and the information retrieved is more accurate, and quantity of information also reduces.
embodiment 4:
In practical application, when the user inputs terms " titanium " from interface load module 203, SQL statement generation module 204 is according to search rule, as shown in Figure 3, in the mineral node of the 4th layer, search is less than the mineral name with " titanium " exact matching, search for the compound node of the 3rd layer, to the node searched in the metallic element node of the second layer with " titanium " exact matching, if degree of correlation parameter r is set to 3, and the number of plies i of the node retrieved is 2, meet r>=i, by this node and descendants's node thereof being put into to the node list, respectively " titanium ", " titania ", " FeTiO
3", " ilmenite ", " dauphinite ", " high titanium slag " and " ilmenite concentrate ".The query statement finally generated is:
" SELECT mineral name; grade; specific inductive capacity, dielectric loss FROM mineral specific inductive capacity table WHERE mineral name=' titanium ' OR mineral name=' titania ' OR mineral name=' FeTiO3 ' OR mineral name=' ilmenite ' OR mineral name=' dauphinite ' OR mineral name=' high titanium slag ' OR mineral name=' ilmenite concentrate ' "
SQL statement generation module 204 is submitted to database retrieval module 205 by this SQL statement and is retrieved in database, can obtain the information of the specific inductive capacity of " titanium " and associated various mineral.When calculating weights, second layer metal element and its product place value of the 3rd stratification compound, without practical significance, are only used for the weights that calculate sequence.The product place value of the metal of the second layer " titanium " is established compound " titania ", " FeTiO of 1, the three layer
3" the product place value get 1; also can get shared ratio in " titanium " compound; the product place value of the mineral node of the 4th layer is the product place value of this mineral reality, according to the weights computation rule, calculates its weights, and obtain final result for retrieval after result set is sorted in internal memory.Result for retrieval shows the user by interface display module 206.
This patent describes by specific implementation process, in the situation that do not break away from this patent scope, can also carry out various conversion and be equal to replacement this patent, therefore, this patent is not limited to disclosed specific implementation process, and should comprise the whole embodiments that fall in this patent claim scope.
Claims (10)
1. a specific inductive capacity database index method, is characterized in that, comprises the steps:
(A) set up conceptional tree: between the concept in the affiliated field of utilization, certain inherent relation factor is set up conceptional tree, described conceptional tree is divided into multilayer, ground floor is root node, except root node, each node in conceptional tree at least comprises value and the weights of search field in one or more database table;
(B) search subscriber term in conceptional tree, to obtain more heterogeneous pass term: after the term that obtains user's input, in described conceptional tree according to the value of certain decision search search field, if exist the value of this node search field and term to be complementary, by rule, this node and junction associated thereof are inserted in a node list, after completing search, return to this node list;
(C) generated query conditional expression: if the node list of returning is not for empty, order travels through the node in the node list, the field that the value of search field and term are complementary forms expression formula by " field name=field value ", between a plurality of expression formulas, with logical connective " OR ", connected, after complete node list of traversal, generate a complete SQL query conditional expression, carry out next step (D), if the node list of returning, for empty, is returned to empty final result for retrieval;
(D) searching database: the querying condition expression formula according to generating, further generate complete SQL query statement, submit to database and retrieved and return results collection;
(E) result for retrieval rearrangement: result set is re-started to sequence by the weights of node in the node list in internal memory, and return to final result for retrieval, empty the node list.
2. specific inductive capacity database index method according to claim 1, it is characterized in that, in step (B), if conceptional tree is the n layer, for improving the degree of correlation of retrieving information, described search strategy is: first search for the n layer, first search for leaf node, if searched for the n layer, the value of search field and the node that term is complementary are arranged, insert the node list by rule, and return to the node list, finish search; If do not search, continue search n-1 layer, by that analogy, until search the root node of the 1st layer, show to search for unsuccessfully, return to empty node list.
3. specific inductive capacity database index method according to claim 1, it is characterized in that, in step (B), for quantizing the degree of correlation, the number of plies according to conceptional tree, introduce degree of correlation parameter, the node that insertion searches in described node list and the rule of junction associated thereof decide by degree of correlation parameter:
Degree of correlation parameter r, the number of plies of conceptional tree is n, the span of degree of correlation parameter r is: 1<r≤n, when at the i layer, searching node, its degree of correlation parameter r >=i,, by this node and the described node list of descendants's Knots inserting thereof, to leaf node, only insert this leaf node in described node list; If r<i, by this node in the described node list of all descendants's Knots insertings of the father node of i layer and father node thereof.
4. specific inductive capacity database index method according to claim 1, it is characterized in that, in step (A), described conceptional tree further is configured to: ground floor is root node, the second layer is metallic element, the 3rd layer is compound, the 4th layer is mineral, the child node of metallic element node is the compound containing this metallic element, the child node of compound node is the mineral containing this compound, except root node, the information of each node is except the field value that comprises mineral name, also comprise molecular formula, grade and weights, the content of the compound of contained its father node of mineral that the grade of mineral node is this node, for number percent, the grade of all the other nodes all is set to 1.
5. according to claim 1,3 or 4 described specific inductive capacity database index methods, it is characterized in that, in step (B), the weights of the node of described conceptional tree are after searching node at every turn, dynamic calculation while inserting the node list, the weights of node calculate like this: when the grade of the node be retrieved is P, its weights W, need to improve weights, W=P+1; And, to its child node, sibling or father node, need to reduce weights, when the grade of a certain node is P
i, the weights that this node is corresponding are W
i=P
i* P.
6. a specific inductive capacity database retrieval system, is characterized in that, this system comprises:
Database, at least comprise mineral specific inductive capacity table and mineral composition table;
Database management module, for the record of the various tables of maintenance data base;
The conceptional tree generation module, set for the automatic product concept of internal memory that is recorded in from existing database;
The interface load module, for inputting interface being provided to the user and obtaining the term of user's input, send term to the SQL statement generation module;
The SQL statement generation module, the term imported into for the reception interface load module, and, under the guidance of conceptional tree, obtain complete SQL query statement, send the SQL query statement to the database retrieval module;
The database retrieval module, for mutual with Database Systems, submit complete SQL statement to Database Systems, and the retrieval set that Database Systems are returned in internal memory by weights rearrangements, send the final result for retrieval after sequence to interface display module;
Interface display module, by final result for retrieval to user-friendly demonstration.
7. specific inductive capacity database retrieval system according to claim 6, is characterized in that, described conceptional tree generation module further comprises: the metallic element administration module, for safeguarding the metallic element list; Compound and mineral information extraction modules, for extracting database compound and mineral information list.
8. according to the described specific inductive capacity database retrieval system of claim 6 or 7, it is characterized in that, when product concept is set, at first the conceptional tree generation module generates root node; The metallic element list provided according to the metallic element administration module again generates the metallic element node of the second layer; Next, the compound and the mineral information list that utilize compound and mineral information extraction modules to provide, generate the compound node of the 3rd layer according to the metallic element that whether comprises the second layer in compound; Finally, according to the compound that whether comprises the 3rd layer in compound and mineral information list, generate the compound node of the 4th layer, and then complete the generation of whole conceptional tree.
9. specific inductive capacity database retrieval system according to claim 6, it is characterized in that, described SQL statement generation module further comprises: the conceptional tree search module, for the search concept tree, search the docuterm segment value that coupling is arranged with term, and the node of coupling and junction associated thereof are inserted in the node list; SQL query expression formula generation module, utilize the node in the node list to generate the SQL query expression formula; SQL statement load module, generate complete SQL statement and send the database retrieval module to according to the SQL query expression formula.
10. specific inductive capacity database retrieval system according to claim 6, it is characterized in that, the database retrieval module further comprises: the database interactive module, for mutual with Database Systems, the connection data storehouse is also submitted the SQL query statement to Database Systems, receives the retrieval set that Database Systems are passed back; The result set order module, for the retrieval set that the database interactive module is returned, the weights rearrangement in conjunction with node in the node list, send the result after sequence to interface display module, and empty the node list.
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