KR20150136300A - Apparatus and method for sorting item using longest increasing subsequence of item group - Google Patents

Abstract

Disclosed are an apparatus and a method for arranging an item using the longest increasing partial subsequence of an item group. The method comprises the following steps: generating item groups by grouping neighboring items among items included in an item list; selecting exceptional groups corresponding to the longest increasing partial subsequence among the item groups; selecting update groups except the exceptional groups from the item groups; and performing an item arrangement for the items by performing an update about the update groups. By grouping various items of the item list, and performing the update by selecting the groups to be updated among the item groups, the method can efficiently use a system by reducing the system operation amount in accordance with the update.

Description

[0001] APPARATUS AND METHOD FOR SORTING ITEM USING LONGEST INCREASING SUBSEQUENCE OF ITEM GROUP [0002]

The present invention relates to an apparatus and method for arranging an item using a longest partial sequence of an item group in which item information can be efficiently updated in a database through item grouping and an item list can be sorted.

The rapid growth of smartphones and tablet PCs is driving the rapid growth of mobile app stores that offer a variety of mobile content and services. These mobile app stores offer a wide variety of mobile items. Accordingly, in order to provide items to the users more conveniently, the items are classified and provided according to the contents of the items, the type of the user terminal, the additional usage fee for using the mobile item, and the like. Also, in such item classification, the exposure ranking in the item list is determined according to the popularity and the latestness of the items, and is provided while updating the exposure rank from time to time.

Accordingly, the app store server that provides a large amount of mobile items needs to update and update the exposure order of the items that are changed frequently from time to time, and to store and manage them in the database. Such a work may cause a heavy load depending on the case, . Nevertheless, reducing the number of mobile items provided by worrying about the system load, or spending a huge amount of money on expanding the system to improve performance, can be a burden for the operators.

Korean Patent Laid-Open No. 10-2001-0025387, published on April 6, 2001 (name: system and method for ranking using the Internet)

It is an object of the present invention to allow the system to perform efficient operations for item update by grouping various items in the item list provided by the store and performing an update by selecting only update groups to be updated among the item groups.

It is also an object of the present invention to provide a system for updating an item by searching for and providing a value when an update performance amount can be minimized when performing an update for a plurality of items at a time among items included in an item list, Reducing the workload.

According to another aspect of the present invention, there is provided an item alignment method comprising: grouping adjacent items among items included in an item list to generate item groups; Selecting exclusion groups corresponding to a longest increasing subsequence among the item groups; Selecting update groups by excluding the exclusion groups from the item groups; And performing an update on the update groups to perform item alignment for the items.

At this time, the step of generating the item groups may group the items whose update order is incremented by 1 among the items included in the item list.

The selecting of the excluded groups may include searching for the longest incremental partial sequence using a start order corresponding to each of the item groups, and extracting groups of items corresponding to the start sequence contained in the longest incremental partial sequence, Groups can be selected.

In this case, in the case where the longest incremental partial sequence is more than two, the step of selecting the exclusion groups may select the exclusion groups considering the size of the group of the item groups corresponding to the start order included in the longest incremental partial sequence have.

At this time, the update may be performed only for the update items corresponding to the update groups among the items.

At this time, performing the item alignment may perform the item alignment using multiple alignment indices.

In this case, the step of performing the item alignment may include arranging the items in the plurality of ordered indexes by using an auxiliary index among the multiple ordered indexes for items having the same primary index among the multiple ordered indexes among the items. Can be performed.

At this time, the update may be performed in consideration of the multiple sort indexes of the items among the items that differ from the update items in the update order by one step.

In this case, if the update index is identical to the main index of the update items and the items whose update order is one step difference, You can do this by changing the secondary index.

At this time, the update may be performed in consideration of the number of the items having the same index and the items differing in the update order by one step from the update items.

According to another aspect of the present invention, there is provided an apparatus for sorting an item, comprising: an item list receiving unit for receiving an item list from a server; An item group generating unit for grouping adjacent items among the items included in the item list to generate item groups; An item update unit updating the update groups among the item groups using a longest increasing subsequence; And an item arrangement unit for performing item arrangement on the items based on the update.

At this time, the item group generating unit may group items in which the update order of the items included in the item list is incremented by one.

In this case, the item update unit may include an excluded group selection unit for selecting excluded groups corresponding to the longest incremental partial sequence among the item groups; And an update group selector for selecting the update groups by excluding the exclusion groups from the item groups.

At this time, the excluded group selection unit searches for the longest incremental partial sequence using the start order corresponding to each of the item groups, and groups the items corresponding to the start sequence included in the longest incremental partial sequence into the excluded groups Can be selected.

In this case, when the longest incremental partial sequence is more than one, the excluded group selection unit may select the exclusion groups considering the size of the group of item groups corresponding to the start order included in the longest incremental partial sequence.

At this time, the item update unit may update only the update items corresponding to the update groups among the items.

At this time, the item arrangement unit may perform the item alignment using multiple alignment indexes.

At this time, the item sorting unit can perform the item sorting using the auxiliary index among the multiple sorting indexes for items having the same primary index among the multiple sorting indexes among the items have.

In this case, the item update unit may update the update items in consideration of the multiple sorting indexes of the items whose update order is one step out of the update items among the items.

According to the present invention, when a plurality of items are updated at a time for a server system that provides contents or items to users, a value obtained when the amount of update can be minimized can be found and provided, The workload of the system can be reduced.

In addition, the present invention can effectively search for items to be updated among the items included in the item list using the item group, thereby significantly reducing the system workload for updating the items.

1 is a flowchart illustrating an item sorting method according to an exemplary embodiment of the present invention.
2 is a diagram illustrating a process of generating groups of items according to an embodiment of the present invention.
3 is a diagram showing an example of the longest incremental partial sequence.
4 is a view showing an item sorting process.
5 is a view showing a list of items according to categories.
FIG. 6 is a view showing an item exposure ranking change.
FIG. 7 is a diagram illustrating an item alignment process using multiple alignment indexes according to an exemplary embodiment of the present invention. Referring to FIG.
8 is a view illustrating an item alignment process using multiple alignment indexes according to another embodiment of the present invention.
9 is a block diagram showing an item alignment apparatus according to an embodiment of the present invention.
10 is a block diagram showing an example of the item update unit shown in FIG.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the following description and the accompanying drawings, detailed description of well-known functions or constructions that may obscure the subject matter of the present invention will be omitted. It should be noted that the same constituent elements are denoted by the same reference numerals as possible throughout the drawings.

The terms and words used in the present specification and claims should not be construed to be limited to ordinary or dictionary meanings and the inventor is not limited to the concept of terminology for describing his or her invention in the best way. It should be interpreted as meaning and concept consistent with the technical idea of the present invention. Therefore, the embodiments described in the present specification and the configurations shown in the drawings are merely the most preferred embodiments of the present invention, and not all of the technical ideas of the present invention are described. Therefore, It is to be understood that equivalents and modifications are possible. Also, the terms first, second, etc. are used for describing various components and are used only for the purpose of distinguishing one component from another component, and are not used to define the components.

1 is a flowchart illustrating an item sorting method according to an exemplary embodiment of the present invention.

Referring to FIG. 1, an item sorting method according to an exemplary embodiment of the present invention may generate item groups by grouping adjacent items among items included in an item list (S110).

At this time, the items may correspond to goods, contents or services, respectively. Products, contents, and services that can be used through a smartphone or a tablet PC can be provided through various types of stores such as an application store, a book store, and a music store, depending on their types. These items can be exposed to users through the item list. In addition, when displaying the item list, the exposure order in the item list can be determined by reflecting the popularity or the latestness of each item included in the item list. Such exposure rankings may change over time as they reflect popularity or up-to-date. Accordingly, in the server system providing the item, the information stored in the system can be updated in real time according to the change of the exposure order of the items in order to provide updated updated information to the users.

However, updating the numerous items every time in order to update the item information stored in the system as described above can put a heavy load on the system. Therefore, when updating the items, the system can perform updates by finding values that can minimize the amount of update work to be processed.

In an actual service, only a relatively small number of items may change the exposure ranking compared to the items included in the item list. Accordingly, in this case, items for which the update order of the adjacent items is increased are grouped for item update and item alignment to perform item alignment.

At this time, the items in the list of items can be grouped by 1 in order of increasing the update order. For example, when items are arranged in the update order of 1-2-3-5-6-4-7-8-9-10-11-12-13-14-15, Item group G1 (1, 2, 3) can be generated by grouping items corresponding to the update order 3 in which the update order is incremented by 1 from the item.

At this time, the update order may be an order in which the items included in the item list are arranged in accordance with the change such as the exposure order change. For example, if the item ranking of the 5th item from the first to fifth items in the item list is changed to 1, the update order may be 5-1-2-3-4. That is, the update order may correspond to a rank change relationship before and after the unit update is performed.

Therefore, G2 (5,6), G3 (4), G4 (7,8,9,10,11,12,13,14,15) are generated in the same way as item group G1 ) Can be further created. These item groups may have start order and group size respectively. For example, in the case of the item group G1 (1,2,3), the start order is '1' and the size of the group may be '3', which is the number of items included in the group. The start order and the size of the group may be used to select update groups to be updated among the group of items.

In addition, the item sorting method according to an embodiment of the present invention may select exclusion groups corresponding to the longest increasing subsequence among the group of items (S120). You can use the longest incremental partial sequence to find the values when the system can reduce the update workload to a minimum. The longest increasing subsequence is the longest of the partial sequences for which the value is increasing. It is the sequence that has the maximum length when selecting numbers that increase from the beginning to the end. Accordingly, items corresponding to the longest incremental sequence corresponding to sequentially increasing numbers can be excluded from the update target, thereby selecting items that can minimize the system load. For example, if five items have an update order of 1-4-2-3-5, then the longest incremental partial sequence in the update sequence may be 1-2-3-5 having four update sequences as a sequence . Items corresponding to the update sequence corresponding to the longest incremental partial sequence 1-2-3-5 can be selected as excluded items.

By using such a longest incremental partial sequence, it is possible to update the item list composed only of items of a certain category corresponding to the change of the exposure order in the list of items in which items for various categories are mixed. For example, it can be assumed that there is an item list A in which items for categories such as game, life, and language are mixed. If the exposure order of the game item a included in the item list A has been changed, the exposure order of the game item a can also be updated in the item list B including only the items corresponding to the game category.

Also, the most efficient algorithm for finding the computational complexity of the currently known longest incremental partial sequence is O (nlog (n)), where n may be the number of input sequences, i. For example, if the item list contains 1024 items, the computational complexity for selecting items to update through the longest incremental sequence in the item list may be O (10,000).

However, if the items are grouped to calculate the computational complexity of the longest incremental partial sequence through the group of items, it may be a value of O (the square of the number of groups). For example, if you create four item groups by grouping items contained in a list of 1024 items, if you calculate the calculation complexity of the longest incremental partial sequence through the group of items, then O (16, the square of the number of groups) ). In this way, since the update items can be selected only by a very small number of calculations in actual calculation, the workload of the system can be reduced by grouping the items and performing item alignment.

At this time, the longest incremental partial sequence may be searched using the start order corresponding to each of the item groups, and the item groups corresponding to the start sequence included in the longest incremental partial sequence may be selected as the excluded groups. For example, it is assumed that item groups G1 (1,2,3), G2 (5,6), G3 (4), G4 (7,8,9,10,11,12,13,14,15) , We can find the longest incremental sequence (1, 5, 7) using '1', '5', '4', and '7' G1 (1,2,3), G2 (5,6), and G4 (7,8,9,10,10) corresponding to the start order included in the longest incremental partial sequence (1,5,7) 11, 12, 13, 14, 15) can be selected as exclusion groups.

In this case, when the longest incremental partial sequence is two or more, the excluded groups can be selected in consideration of the size of the group of item groups corresponding to the start order included in the longest incremental partial sequence. For example, it is assumed that item groups G1 (1,2,3), G2 (5,6), G3 (4), G4 (7,8,9,10,11,12,13,14,15) Assuming that the two longest incremental parts (1, 5, 7) and (1, 4, 7) such as (1, 5, 7) and You can find the sequence. In this case, since the group of items corresponding to the start order included in the longest incremental partial sequence is selected as the exclusion groups, selection using the longest incremental partial sequences (1,5,7) and (1,4,7) The excluded groups may be different. However, the present invention is intended to provide an update value for performing less work in the system when updating an item, and more items can be selected from values to be excluded from the update. Therefore, exclusion groups can be selected using (1,5,7) which can exclude more items from the two longest incremental partial sequences.

As described above, the most efficient algorithm of the currently known longest incremental partial sequence is O (nlog (n)), where n may be the number of input permutations. In the present invention, the O (nlog (n)) algorithm may not be available because the items are grouped. Therefore, it is possible to use a method of solving the longest incremental partial sequence by dynamic programming. Since the actual operation is calculated by only the size of each group and the start order, it is possible to drastically reduce the operation. For example, the method of selecting update groups by finding the longest partial sequence of item groups is classified as when each group belongs to update groups or exclusion groups, so the calculation complexity is O (the square of the number of groups) . In fact, solutions that do not consist solely of net incrementing groups, that is update groups, are excluded from the set of solutions for the longest incremental partial sequence and the actual computation may be possible only with significantly fewer operations than O (the square of the number of groups).

In addition, the item sorting method according to an embodiment of the present invention may select update groups by excluding excluded groups from item groups (S130). In case of updating due to the change of the exposure ranking of the items included in the item list, it is possible to smoothly operate the system by minimizing the workload of the system due to the update. Therefore, it is possible to select only the update groups for updating only the remaining item groups excluding the exclusion groups selected using the longest incremental partial sequence among the item groups generated by using the items included in the item list. For example, if the update order using the start order of the group of items is 1-5-2-3-4, then the longest incremental partial sequence of the update order using the start order corresponds to the update order 1-2-3-4 May be sorted into exclusion groups. Therefore, only the item group having the start order corresponding to the remaining update order 5 can be selected as the update group.

In addition, the item alignment method according to an exemplary embodiment of the present invention may update the update groups to perform item alignment for the items (S140). Update groups of item groups can be updated. In addition, it is possible to update the list of items in the server and provide them to the users by performing item sorting on the items in accordance with the update.

At this time, the update may be performed only for the update items corresponding to the update groups among the items. For example, assuming that there are five items with the exposure rankings from the first to the fifth rank, the item rank of the fifth item can be changed to the rank one according to the change of the exposure ranking. If you use the existing update method, you may need to update 5 items in the first place and update the items in the first to fourth items so that they are added one by one. However, this update method may not be a suitable method for use in a store providing a large number of contents and the like because it can load the system when the number of items is large. Therefore, the items from the first to the fourth through the longest incremental sequence can be selected as excluded items to be excluded from the update operation. In addition, only the fifth item excluding the excluded items among the items can be selected as an update item, and the updating can be performed to significantly reduce the workload of the system.

At this time, item alignment can be performed using multiple alignment indexes. In order to arrange the item list of contents to be provided to users in a list of items such as the present invention or a store providing various contents, a single sorting index can be generally used. However, a very complicated operation procedure may be required to update the items and contents in which the exposure order is changed frequently using a single sorting index, and sort the item list. Accordingly, in the present invention, it is possible to more effectively update an item or content and perform item alignment of items in an environment in which an exposure order is frequently changed by using multiple sort indexes through two or more indexes. For example, you can sort by "order by C1, C2, ..., Cn" in SQL select using n sort indices from C1 to Cn. It is possible to perform sorting using the first sorting index C1 and arrange the items using the sorted indexes C2, C3, ..., Cn step by step. In addition, C2, the second sorting index, can perform item sorting only through the value of C2 without updating the value of C1, the first sorting index.

At this time, item alignment can be performed using an auxiliary index among multiple ordered indexes for items having the same primary index among multiple ordered indexes among the items. The primary index may be the first sorting index among the multiple sorting indices, and the secondary index may be the second sorting index. For example, A (1,0), B (2,0), C (3,0), D (0,0), and A 4,0), and E (5,0). If item E is located in the next step of item A in the update order, item E can update multiple ordered indexes in the form of E (2,0), taking into account the primary index of item A. However, if the updating is performed in this way, the sorting index of the updated item E is the same as that of the item B (2,0). Therefore, it is possible to perform item alignment smoothly in the system by using the auxiliary index as in the form of E (2, -1).

In this case, the update can be performed in consideration of the update items among the items and the multiple sort indexes of the items whose update order differs by one step. For example, suppose that there are five items A (1,0), B (2,0), C (3,0), D (4,0), E (5,0) (2, -1) and E (1, 1) when it is changed to be located in the next order of the item A in the update order. E (2, -1) may be an update form of multiple ordered indexes corresponding to item B located in the next step of item E in the update order. In addition, E (1,1) may be an update form of multiple ordered indexes corresponding to item A in the previous step of item E in the update order.

At this time, the update is performed by changing any one of the update items and the items whose update order is one step difference, when the update items and the main indexes of the items whose update orders are different one by one are the same can do. For example, when it is assumed that there are three items A (1,0), B (1,1), C (2,0), and the item C is changed to be positioned in the next order of the item A in the update order It may be difficult to update only the multiple sorting indices of item C to arrange the items. Because the main indexes of items A and B are the same and the auxiliary indexes are '0' and '1', the auxiliary index of item C can not be set to an integer value between '0' and '1'. Therefore, the auxiliary index of item B can be updated together with the form of A (1,0), C (1,1), B (1,2). Item A can be sorted by updating the auxiliary index of Item A such that A (1, -1), C (1,0), B (1,1)

At this time, the update can be performed in consideration of the number of items having the same index as the items whose update order is one step difference from the update items. For example, suppose there are five items A (1, -1), B (1,0), C (1,1), D (2,0), E (3,0) (1, 2) and D (2, -1) in the case where the update order is changed to be located in the next order of the item C in the update order. If multiple ordered indexes are updated in the form of E (1,2), item alignment can be performed using the auxiliary indexes of the four items A, B, C, and E that have the same primary index when sorting the items. However, if multiple sort indexes are updated in the form of E (2, -1), item alignment is performed using the secondary indexes of the two items E and D having the same main index at the time of sorting the items. Can be reduced. Therefore, when considering the number of items having the same index as the main index, it is possible to reduce the workload of the system by updating the multi-sorting indexes with a relatively small number of items having the same main index.

By using such an item sorting method, only the update group to be updated among the item groups is selected and updated, so that the system can help efficient operation for item update.

2 is a diagram illustrating a process of generating groups of items according to an embodiment of the present invention.

Referring to FIG. 2, an array 210 of items indicating the state before the exposure order of the items is changed in the item list of the store can be confirmed.

The order of exposures of the items corresponding to the fourth item in the item arrangement 210 may be changed and the arrangement may be changed as in the update order 220. [

At this time, item groups can be created by grouping the items whose update order is incremented by 1 among the items included in the update order 220. [ For example, an item corresponding to 1, which is the first order of the update order 220, and an item corresponding to 3, in which the update order is incremented by 1, can be grouped. Then, an item corresponding to 5, which is the next update order, can be further grouped to an item corresponding to 6 whose update order is incremented by 1. In this way, item groups G1 231, G2 232, G3 233 and G4 234 can be created by grouping.

In this case, the longest incremental partial sequence (1,5,7) can be found by using the start order of the item groups '1', '5', '4', and '7' Item groups corresponding to the included start order can be selected as exclusion groups. In addition, although the partial sequence (1, 4, 7) is also the longest incremental sequence, when the size of the item group is taken into account, Can be used to select exclusion groups.

At this time, if the excluded items are selected using the longest incremental partial sequence without grouping the items included in the update order 220, the computational complexity may be O (10,000) through the O (nlog (n)) algorithm. However, if the items of the update order 220 are grouped and the calculation complexity of the longest incremental partial sequence is calculated through the item groups, it may be 0 (16), which is the value of O (the square of the number of groups). In this way, since the update items can be selected only by a very small number of calculations in actual calculation, it is possible to reduce the workload of the system by grouping items to perform item alignment.

3 is a diagram showing an example of the longest incremental partial sequence.

Referring to FIG. 3, it is assumed that the numbers included in the general sequence 310 are each an item. If the arrangement of the numbers included in the general sequence 310 is assumed to be the exposure order in the item list, the exposure order of the items can be changed in the same arrangement as the variation sequence 320 due to the variation in the exposure order.

In this case, the order in which the items included in the item list are arranged according to the change such as the change in the exposure order of the items may be referred to as an update order. In FIG. 3, the arrangement corresponding to the variation sequence 320 can be referred to as an update sequence.

At this time, the excluded items to be excluded from the update among the items included in the item list through the longest partial sequence of the update order can be selected. The longest incremental partial sequence is the longest of the partial sequences for which the value is incremented. It is the sequence that has the maximum length when selecting a number that increases from the beginning to the end. For example, if the longest incremental partial sequence is found in the fluctuation sequence 320, it may be 1-2-3-5-6. Accordingly, the items whose update order corresponds to the longest incremental partial sequence can be selected by the excluded item 330. [

At this time, the items excluding the excluded items 330 among the items corresponding to the update sequence of the fluctuation sequence 320 can be selected as update items. Accordingly, only the update items among the items included in the item list can be updated. For example, in FIG. 3, the items of update order of the variation sequence 320 corresponding to 4 and 7 can be updated. As described above, by updating only the update items to be updated among the items included in the item list using the longest incremental partial sequence, the update workload to be processed by the system can be minimized.

4 is a view showing an item sorting process.

Referring to FIG. 4, in the item aligning process, the 'First Avenger' item, which is located at the tenth place in the item list, is updated to the top, so that the nine items from the first to ninth places are updated Able to know. During this process, the system can perform a total of 10 updates to sort the list of items.

In this case, although an item list including only 10 items is updated and arranged through an item sorting process in FIG. 4, in a store that actually provides contents or items corresponding to various categories, a list of items having a large number of contents or items 4 < / RTI > In addition, since a list of various kinds of items may exist depending on the category, item alignment can be performed from time to time for each item list. For example, if the lowest ranked item is updated to the top in the list of items consisting of 10000 items, as shown in FIG. 4, the system needs to perform a total of 10,000 update tasks, which is a cause of providing a large load to the system . Also, for example, if there is an item list in which items corresponding to 10 kinds of categories are mixed, it may be necessary to perform such item alignment for a total of 11 item lists from the item list according to each category. Such updating and item sorting process also requires a large amount of computation to the system, so it may not be appropriate as an item sorting method of a system that needs to provide a service reflecting latest information to users.

5 is a view showing a list of items according to categories.

Referring to FIG. 5, a list of items according to categories may include an entire item list 510 in which items corresponding to various categories are mixed, and a category item list 520 composed of only items corresponding to a specific category.

The full item list 510 may be a list of items organized using items for all categories. Items included in the full item list 510 can be changed in the exposure order in the entire item list 510 according to the popularity or the latestness of the items irrespective of each category.

At this time, as the exposure order of a specific item is changed in the full item list 510, the exposure order may be changed in the category item list 520 composed of only items corresponding to the category of the item. In order to apply the updated items to the category item list 520 in the same manner as the exposure order is changed in the entire item list 510, the longest incremental partial sequence for the update order can be used in the present invention.

The update order may be an order in which the items included in the item list are arranged according to a change such as an item exposure ranking change. For example, when it is assumed that item A corresponds to a game category located at 16th in the entire item list 510, it can be assumed that item A is ranked 10th because of exposure rank variation. In this case, the update order may be 1-2-3-4-5-6-7-8-9-16-10-11-12-13-14-15. Therefore, we can find the longest incremental sequence for such an update sequence and update only the item A corresponding to 16 that does not correspond to the longest incremental sequence.

Also in the category item list 520 for the game category, an update order such as 1-2-6-8-16-11-12-13 may be created due to the change in the exposure order of item A. In this case as well, we can find the longest incremental partial sequence and update only the item A corresponding to 16 that does not correspond to the longest incremental partial sequence.

By updating the items and arranging the items using the longest incremental partial sequence for the update sequence in the change of the exposure order of the items, the various item lists can be updated effectively as well.

FIG. 6 is a view showing an item exposure ranking change.

Referring to FIG. 6, the item list 610 before changing the exposure ranking and the item list 620 after changing the exposure ranking in which the exposure rank of many items are changed can be checked.

The exposure order of the items may be changed according to the popularity or freshness of the items included in the item list 610 before the exposure ranking change. In this case, the exposure order may be changed only for a small number of items, but the exposure order may be changed for a large number of items such as the item list 620 after the exposure order change. When the exposure order of the items is changed in a complicated manner, all the items can be updated to perform item alignment.

However, even with complicated changes, the longest incremental sequence for the update order can be used to find and update only the items to be updated without updating all the items. For example, it is possible to find the longest incremental partial sequence by updating the order of the numbers listed in the item list 620 after changing the exposure rank. For example, longest incremental sequences such as 3-4-5-6-7-8, 2-4-5-6-7-8, and 1-4-5-6-7-8 can be found. Accordingly, the update item to be updated can be selected by selecting one of the longest incremental partial sequences and selecting an item corresponding to the selected longest incremental partial sequence as an excluded item. In the case of such a change in the complex exposure ranking, the update workload of the system can be reduced by determining and updating the minimum items to be updated without updating all the items included in the item list using the longest incremental partial sequence.

FIG. 7 is a diagram illustrating an item alignment process using multiple alignment indexes according to an exemplary embodiment of the present invention. Referring to FIG.

Referring to FIG. 7, an item alignment process using multiple alignment indexes according to an exemplary embodiment of the present invention includes an item ordering process It can be seen that the change has been made.

After confirming the item list 720 after the rank change, item E moves to the next item A in the update order, and the main index and the auxiliary index are updated to (2, -1), respectively. When the items are sorted using the multiple sort indexes, the item B having the same main index as the item E of the item list 720 after the ranking change can be sorted using the auxiliary index. For example, as shown in FIG. 7, an item E having an auxiliary index of '-1' may be positioned in the previous order in the item list rather than the item B.

Item alignment can also be performed by updating the main index and the auxiliary index of item E to (1,1), respectively. In such a case, the item A having the same main index as the item E of the item list 720 after the rank change can be sorted using the auxiliary index. For example, item E with an auxiliary index of '1' may be placed in the next order of item A in the item list.

At this time, when the main indexes of the items whose update order is different by one step are identical, the auxiliary indexes of the update items and the items whose update order are different one by one are changed to update items You can update it. For example, if it is assumed that item D in the item list 720 after the ranking change moves to the next item E in the update order, item D can be updated while updating the auxiliary index of either item E or item B together have. If you update the auxiliary index of item E together, you can update multiple sort indices in the form E (2, -2), D (2, -1), B (2,0) Also, if you update the auxiliary index of item B together, you can update multiple ordered indexes in the form E (2, -1), D (2,0), B (2,1)

8 is a view illustrating an item alignment process using multiple alignment indexes according to another embodiment of the present invention.

Referring to FIG. 8, an item alignment process using multiple alignment indexes according to another exemplary embodiment of the present invention includes a process of arranging items C included in an item list 810 using two sorted indexes You can see that the update is done.

If item list 820 using three sort indexes is checked, item C is updated in (2, -1, -1) by using second auxiliary index while moving in the next order of item E in the update order have. Thus, even if the main index and the first auxiliary index are the same, the update can be simply performed using the second auxiliary index.

At this time, it is also possible to update in the form of C (2, -1), D (2, -2) without using the second auxiliary index. However, if the number of items having the same main index of '2' is large, the first auxiliary index of many items may be updated in some cases. Therefore, as shown in FIG. 8, You can update it.

9 is a block diagram showing an item alignment apparatus according to an embodiment of the present invention.

9, an item sorting apparatus 900 according to an embodiment of the present invention includes an item list receiving unit 910, an item group creating unit 920, an item updating unit 930, an item arranging unit 940, And an item database 950.

The item list receiving unit 910 can receive the item list from the server. For example, an item list can be received from a server system that manages a store that provides contents and items that can be executed by using an app store providing a mobile application, a smart phone, a tablet PC, or the like. Such a list of items may be a list of various items ranging from a list of items in which items for all categories are mixed to a list of items for categories.

The item group generation unit 920 may group items adjacent to the items included in the item list to generate item groups.

At this time, the items may correspond to goods, contents or services, respectively. Products, contents, and services that can be used through a smartphone or a tablet PC can be provided through various types of stores such as an application store, a book store, and a music store, depending on their types. These items can be exposed to users through the item list. In addition, when displaying the item list, the exposure order in the item list can be determined by reflecting the popularity or the latestness of each item included in the item list. Such exposure rankings may change over time as they reflect popularity or up-to-date. Accordingly, in the server system providing the item, the information stored in the system can be updated in real time according to the change of the exposure order of the items in order to provide updated updated information to the users.

However, updating the numerous items every time in order to update the item information stored in the system as described above can put a heavy load on the system. Therefore, when updating the items, the system can perform updates by finding values that can minimize the amount of update work to be processed.

In an actual service, only a relatively small number of items may change the exposure rank compared to the items included in the item list. Therefore, in order to arrange items suitable for this case, it is possible to perform a step for item alignment by grouping items whose update order is increased among adjacent items.

At this time, the items in the list of items can be grouped by 1 in order of increasing the update order. For example, when items are arranged in the update order of 1-2-3-5-6-4-7-8-9-10-11-12-13-14-15, Item group G1 (1, 2, 3) can be generated by grouping items corresponding to the update order 3 in which the update order is incremented by 1 from the item.

At this time, the update order may be an order in which the items included in the item list are arranged in accordance with the change such as the exposure order change. For example, if the item ranking of the 5th item from the first to fifth items in the item list is changed to 1, the update order may be 5-1-2-3-4. That is, the update order may correspond to a rank change relationship before and after the unit update is performed.

Therefore, G2 (5,6), G3 (4), G4 (7,8,9,10,11,12,13,14,15) are generated in the same way as item group G1 ) Can be further created. These item groups may have start order and group size respectively. For example, in the case of the item group G1 (1,2,3), the start order is '1' and the size of the group may be '3', which is the number of items included in the group. The start order and the size of the group may be used to select update groups to be updated among the group of items.

The item update unit 930 may update the update groups among the item groups using the longest increasing subsequence.

At this time, the excluded groups corresponding to the longest incremental partial sequence among the item groups can be selected. You can use the longest incremental partial sequence to find the values when the system can reduce the update workload to a minimum. The longest incremental partial sequence is the longest of the partial sequences for which the value is incremented. It is the sequence that has the maximum length when selecting a number that increases from the beginning to the end. Accordingly, items corresponding to the longest incremental sequence corresponding to sequentially increasing numbers can be excluded from the update target, thereby selecting items that can minimize the system load. For example, if five items have an update order of 1-4-2-3-5, then the longest incremental partial sequence in the update sequence may be 1-2-3-5 having four update sequences as a sequence . Items corresponding to the update sequence corresponding to the longest incremental partial sequence 1-2-3-5 can be selected as excluded items.

By using such a longest incremental partial sequence, it is possible to update the item list composed only of items of a certain category corresponding to the change of the exposure order in the list of items in which items for various categories are mixed. For example, it can be assumed that there is an item list A in which items for categories such as game, life, and language are mixed. If the exposure order of the game item a included in the item list A has been changed, the exposure order of the game item a can also be updated in the item list B including only the items corresponding to the game category.

Also, the most efficient algorithm for finding the computational complexity of the currently known longest incremental partial sequence is O (nlog (n)), where n may be the number of input sequences, i. For example, if the item list contains 1024 items, the computational complexity for selecting items to update through the longest incremental sequence in the item list may be O (10,000).

However, if the items are grouped to calculate the computational complexity of the longest incremental partial sequence through the group of items, it may be a value of O (the square of the number of groups). For example, if you create four item groups by grouping items contained in a list of 1024 items, if you calculate the calculation complexity of the longest incremental partial sequence through the group of items, then O (16, the square of the number of groups) ). In this way, since the update items can be selected only by a very small number of calculations in actual calculation, the workload of the system can be reduced by grouping the items and performing item alignment.

At this time, the longest incremental partial sequence may be searched using the start order corresponding to each of the item groups, and the item groups corresponding to the start sequence included in the longest incremental partial sequence may be selected as the excluded groups. For example, it is assumed that item groups G1 (1,2,3), G2 (5,6), G3 (4), G4 (7,8,9,10,11,12,13,14,15) , We can find the longest incremental sequence (1, 5, 7) using '1', '5', '4', and '7' G1 (1,2,3), G2 (5,6), and G4 (7,8,9,10,10) corresponding to the start order included in the longest incremental partial sequence (1,5,7) 11, 12, 13, 14, 15) can be selected as exclusion groups.

In this case, when the longest incremental partial sequence is two or more, the excluded groups can be selected in consideration of the size of the group of item groups corresponding to the start order included in the longest incremental partial sequence. For example, it is assumed that item groups G1 (1,2,3), G2 (5,6), G3 (4), G4 (7,8,9,10,11,12,13,14,15) Assuming that the two longest incremental parts (1, 5, 7) and (1, 4, 7) such as (1, 5, 7) and You can find the sequence. In this case, since the group of items corresponding to the start order included in the longest incremental partial sequence is selected as the exclusion groups, selection using the longest incremental partial sequences (1,5,7) and (1,4,7) The excluded groups may be different. However, the present invention is intended to provide an update value for performing less work in the system when updating an item, and more items can be selected from values to be excluded from the update. Therefore, exclusion groups can be selected using (1,5,7) which can exclude more items from the two longest incremental partial sequences.

As described above, the most efficient algorithm of the currently known longest incremental partial sequence is O (nlog (n)), where n may be the number of input permutations. In the present invention, the O (nlog (n)) algorithm may not be available because the items are grouped. Therefore, it is possible to use a method of solving the longest incremental partial sequence by dynamic programming. Since the actual operation is calculated by only the size of each group and the start order, it is possible to drastically reduce the operation. For example, the method of selecting update groups by finding the longest partial sequence of item groups is classified as when each group belongs to update groups or exclusion groups, so the calculation complexity is O (the square of the number of groups) . In fact, solutions that do not consist solely of net incrementing groups, that is update groups, are excluded from the set of solutions for the longest incremental partial sequence and the actual computation may be possible only with significantly fewer operations than O (the square of the number of groups).

At this time, the update groups can be selected by excluding the exclusion groups from the item groups. In case of updating due to the change of the exposure ranking of the items included in the item list, it is possible to smoothly operate the system by minimizing the workload of the system due to the update. Therefore, it is possible to select only the update groups for updating only the remaining item groups excluding the exclusion groups selected using the longest incremental partial sequence among the item groups generated by using the items included in the item list. For example, if the update order using the start order of the group of items is 1-5-2-3-4, then the longest incremental partial sequence of the update order using the start order corresponds to the update order 1-2-3-4 May be sorted into exclusion groups. Therefore, only the item group having the start order corresponding to the remaining update order 5 can be selected as the update group.

At this time, only the update items corresponding to the update groups among the items can be updated. For example, assuming that there are five items with the exposure rankings from the first to the fifth rank, the item rank of the fifth item can be changed to the rank one according to the change of the exposure ranking. If you use the existing update method, you may need to update 5 items in the first place and update the items in the first to fourth items so that they are added one by one. However, this update method may not be a suitable method for use in a store providing a large number of contents and the like because it can load the system when the number of items is large. Therefore, the items from the first to the fourth through the longest incremental sequence can be selected as excluded items to be excluded from the update operation. In addition, only the fifth item excluding the excluded items among the items can be selected as an update item, and the updating can be performed to significantly reduce the workload of the system.

At this time, the update items can be updated in consideration of multiple update indexes among the items and multiple sort indexes of items whose update order is one step difference. The primary index among the multiple sorted indexes may be the first ordered index among the multiple-indexed indexes, and the auxiliary index among the multiple ordered indexes may be the second sorted index. For example, when the main index and auxiliary index of each item are expressed in the form of (x, y) in order, five items A (1,0), B (2,0), C (3,0) , D (4,0), and E (5,0). At this time, if the item E is changed to be positioned in the next order of the item A in the update order, the multi-sort indexes of the item E are updated in the form of E (2, -1) and E . E (2, -1) may be an update form of multiple ordered indexes corresponding to item B located in the next step of item E in the update order. In addition, E (1,1) may be an update form of multiple ordered indexes corresponding to item A in the previous step of item E in the update order.

At this time, when the main indexes of the items whose update order is different by one step are identical, the auxiliary indexes of the update items and the items whose update order are different one by one are changed to update items You can update it. For example, when it is assumed that there are three items A (1,0), B (1,1), C (2,0), and the item C is changed to be positioned in the next order of the item A in the update order It may be difficult to update only the multiple sorting indices of item C to arrange the items. Because the main indexes of items A and B are the same and the auxiliary indexes are '0' and '1', the auxiliary index of item C can not be set to an integer value between '0' and '1'. Therefore, the auxiliary index of item B can be updated together with the form of A (1,0), C (1,1), B (1,2). Item A can be sorted by updating the auxiliary index of Item A such that A (1, -1), C (1,0), B (1,1)

At this time, the update items can be updated in consideration of the number of items having the same index as the items whose update order is one step difference from the update items. For example, suppose there are five items A (1, -1), B (1,0), C (1,1), D (2,0), E (3,0) (1, 2) and D (2, -1) in the case where the update order is changed to be located in the next order of the item C in the update order. If multiple ordered indexes are updated in the form of E (1,2), item alignment can be performed using the auxiliary indexes of the four items A, B, C, and E that have the same primary index when sorting the items. However, if multiple sort indexes are updated in the form of E (2, -1), item alignment is performed using the secondary indexes of the two items E and D having the same main index at the time of sorting the items. Can be reduced. Therefore, when considering the number of items having the same index as the main index, it is possible to reduce the workload of the system by updating the multi-sorting indexes with a relatively small number of items having the same main index.

The item arrangement unit 940 can perform item alignment on the items based on the update. As the update items among the items are updated, the server can also perform item sorting to update the list of items to be exposed to users.

At this time, item alignment can be performed using multiple alignment indexes. In order to arrange the item list of contents to be provided to users in a list of items such as the present invention or a store providing various contents, a single sorting index can be generally used. However, a very complicated operation procedure may be required to update the items and contents in which the exposure order is changed frequently using a single sorting index, and sort the item list. Accordingly, in the present invention, it is possible to more effectively update an item or content and perform item alignment of items in an environment in which an exposure order is frequently changed by using multiple sort indexes through two or more indexes. For example, you can sort by "order by C1, C2, ..., Cn" in SQL select using n sort indices from C1 to Cn. It is possible to perform sorting using the first sorting index C1 and arrange the items using the sorted indexes C2, C3, ..., Cn step by step. In addition, C2, the second sorting index, can perform item sorting only through the value of C2 without updating the value of C1, the first sorting index.

At this time, item alignment can be performed using an auxiliary index among multiple ordered indexes for items having the same primary index among multiple ordered indexes among the items. The primary index may be the first sorting index among the multiple sorting indices, and the secondary index may be the second sorting index. For example, A (1,0), B (2,0), C (3,0), D (0,0), and A 4,0), and E (5,0). If item E is located in the next step of item A in the update order, item E can update multiple ordered indexes in the form of E (2,0), taking into account the primary index of item A. However, if the updating is performed in this way, the sorting index of the updated item E is the same as that of the item B (2,0). Therefore, it is possible to perform item alignment smoothly in the system by using the auxiliary index as in the form of E (2, -1).

The item database 950 may store information of items included in the item list. In addition, information of the items updated by the item updating unit 930 and information of the item list sorted by the item aligning unit 940 can be stored.

In the case where the plurality of items are updated at a time using the item sorting apparatus 900, the amount of the update operation can be minimized and the value of the system operation amount due to the item update can be reduced have.

10 is a block diagram showing an example of the item update unit shown in FIG.

Referring to FIG. 10, the item update unit 930 shown in FIG. 9 may include an excluded group selector 1010 and an update group selector 1020.

The excluded group selection unit 1010 can select excluded groups corresponding to the longest incremental partial sequence among the item groups. You can use the longest incremental partial sequence to find the values when the system can reduce the update workload to a minimum. The longest incremental partial sequence is the longest of the partial sequences for which the value is incremented. It is the sequence that has the maximum length when selecting a number that increases from the beginning to the end. Accordingly, items corresponding to the longest incremental sequence corresponding to sequentially increasing numbers can be excluded from the update target, thereby selecting items that can minimize the system load. For example, if five items have an update order of 1-4-2-3-5, then the longest incremental partial sequence in the update sequence may be 1-2-3-5 having four update sequences as a sequence . Items corresponding to the update sequence corresponding to the longest incremental partial sequence 1-2-3-5 can be selected as excluded items.

By using such a longest incremental partial sequence, it is possible to update the item list composed only of items of a certain category corresponding to the change of the exposure order in the list of items in which items for various categories are mixed. For example, it can be assumed that there is an item list A in which items for categories such as game, life, and language are mixed. If the exposure order of the game item a included in the item list A has been changed, the exposure order of the game item a can also be updated in the item list B including only the items corresponding to the game category.

Also, the most efficient algorithm for finding the computational complexity of the currently known longest incremental partial sequence is O (nlog (n)), where n may be the number of input sequences, i. For example, if the item list contains 1024 items, the computational complexity for selecting items to update through the longest incremental sequence in the item list may be O (10,000).

However, if the items are grouped to calculate the computational complexity of the longest incremental partial sequence through the group of items, it may be a value of O (the square of the number of groups). For example, if you create four item groups by grouping items contained in a list of 1024 items, if you calculate the calculation complexity of the longest incremental partial sequence through the group of items, then O (16, the square of the number of groups) ). In this way, since the update items can be selected only by a very small number of calculations in actual calculation, the workload of the system can be reduced by grouping the items and performing item alignment.

At this time, the longest incremental partial sequence may be searched using the start order corresponding to each of the item groups, and the item groups corresponding to the start sequence included in the longest incremental partial sequence may be selected as the excluded groups. For example, it is assumed that item groups G1 (1,2,3), G2 (5,6), G3 (4), G4 (7,8,9,10,11,12,13,14,15) , We can find the longest incremental sequence (1, 5, 7) using '1', '5', '4', and '7' G1 (1,2,3), G2 (5,6), and G4 (7,8,9,10,10) corresponding to the start order included in the longest incremental partial sequence (1,5,7) 11, 12, 13, 14, 15) can be selected as exclusion groups.

In this case, when the longest incremental partial sequence is two or more, the excluded groups can be selected in consideration of the size of the group of item groups corresponding to the start order included in the longest incremental partial sequence. For example, it is assumed that item groups G1 (1,2,3), G2 (5,6), G3 (4), G4 (7,8,9,10,11,12,13,14,15) Assuming that the two longest incremental parts (1, 5, 7) and (1, 4, 7) such as (1, 5, 7) and You can find the sequence. In this case, since the group of items corresponding to the start order included in the longest incremental partial sequence is selected as the exclusion groups, selection using the longest incremental partial sequences (1,5,7) and (1,4,7) The excluded groups may be different. However, the present invention is intended to provide an update value for performing less work in the system when updating an item, and more items can be selected from values to be excluded from the update. Therefore, exclusion groups can be selected using (1,5,7) which can exclude more items from the two longest incremental partial sequences.

As described above, the most efficient algorithm of the currently known longest incremental partial sequence is O (nlog (n)), where n may be the number of input permutations. In the present invention, the O (nlog (n)) algorithm may not be available because the items are grouped. Therefore, it is possible to use a method of solving the longest incremental partial sequence by dynamic programming. Since the actual operation is calculated by only the size of each group and the start order, it is possible to drastically reduce the operation. For example, the method of selecting update groups by finding the longest partial sequence of item groups is classified as when each group belongs to update groups or exclusion groups, so the calculation complexity is O (the square of the number of groups) . In fact, solutions that do not consist solely of net incrementing groups, that is update groups, are excluded from the set of solutions for the longest incremental partial sequence and the actual computation may be possible only with significantly fewer operations than O (the square of the number of groups).

The update group selection unit 1020 may select update groups by excluding excluded groups from the item groups. In case of updating due to the change of the exposure ranking of the items included in the item list, it is possible to smoothly operate the system by minimizing the workload of the system due to the update. Therefore, it is possible to select only the update groups for updating only the remaining item groups excluding the exclusion groups selected using the longest incremental partial sequence among the item groups generated by using the items included in the item list. For example, if the update order using the start order of the group of items is 1-5-2-3-4, then the longest incremental partial sequence of the update order using the start order corresponds to the update order 1-2-3-4 May be sorted into exclusion groups. Therefore, only the item group having the start order corresponding to the remaining update order 5 can be selected as the update group.

The item alignment method according to the present invention can be implemented in the form of a program command that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions recorded on the medium may be those specially designed and configured for the present invention or may be available to those skilled in the art of computer software. Examples of computer-readable media include magnetic media such as hard disks, floppy disks and magnetic tape; optical media such as CD-ROMs and DVDs; magnetic media such as floppy disks; Includes all types of hardware devices that are specially configured to store and execute magneto-optical media and program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions may include machine language code such as those generated by a compiler, as well as high-level language code that may be executed by a computer using an interpreter or the like. Such a hardware device may be configured to operate as one or more software modules to perform the operations of the present invention, and vice versa.

As described above, the arrangement and method of arranging items using the longest incremental partial sequence of an item group according to the present invention are not limited to the configurations and methods of the embodiments described above, All or some of the embodiments may be selectively combined.

According to the present invention, item groups are created by grouping adjacent items among the items included in the item list, and exclusion groups corresponding to the longest incremental partial sequence of the item groups are selected and exclusion groups are excluded from the item groups It is possible to sort the update groups and perform an update on the update groups to perform item sorting on the items. Furthermore, the system load can be reduced by reducing the workload of the system without a hardware upgrade, which can reduce the cost of managing the system. In addition, when the system operation is performed separately, the work can be processed more smoothly.

210: Arrangement of Items 220: Update Order
231, 232, 233, 234: Item group 310: General sequence
320: Variable sequence 330: Excluded items
510: All Item List 520: Category Item List
610: List of items before change of exposure ranking
620: Item list after changing exposure rank
710: Item list before ranking change 720: Item list after ranking change
810: List of items using two sorting indexes
820: List of items using 3 sorting indexes
900: Item aligning device 910: Item list receiving unit
920: Item group generating unit 930:
940: Item arranging unit 950: Item database
1010: Exclusion group selection unit 1020: Update group selection unit

Claims (20)

Grouping adjacent items among the items included in the item list to generate item groups;
Selecting exclusion groups corresponding to a longest increasing subsequence among the item groups;
Selecting update groups by excluding the exclusion groups from the item groups; And
Performing an update on the update groups to perform item alignment on the items
≪ / RTI > The method according to claim 1,
The step of generating the group of items
Wherein items in the list of items that are incremented by 1 in the update order are grouped. The method of claim 2,
The step of selecting the exclusion groups
And the item group corresponding to the start order included in the longest incremental partial sequence is selected as the exclusion groups. How to sort. The method of claim 3,
The step of selecting the exclusion groups
Wherein when the longest incremental partial sequence is two or more, the excluded groups are selected in consideration of the size of the group of item groups corresponding to the start order included in the longest incremental partial sequence. The method of claim 2,
The update
Wherein the updating is performed only for update items corresponding to the update groups of the items. The method of claim 5,
The step of performing the item alignment
Wherein the item alignment is performed using multiple alignment indices. The method of claim 6,
The step of performing the item alignment
Wherein the item alignment is performed using an auxiliary index among the multiple alignment indexes for items having the same primary index among the multiple sorting indexes among the items. . The method of claim 7,
The update
Wherein the updating is performed in consideration of the multiple sorting indexes of the items in which the updating order of the updating items is one step out of the items. The method of claim 8,
The update
If the main indexes of the items differing by one step are different from each other, the auxiliary indexes of any one of the update items and the items whose update order differ by one step are changed The method comprising the steps of: The method of claim 9,
The update
Wherein the updating step is performed in consideration of the number of items having the same index and the items whose difference is one step difference between the update items and the update order. An item list receiving unit for receiving an item list from a server;
An item group generating unit for grouping adjacent items among the items included in the item list to generate item groups;
An item update unit updating the update groups among the item groups using a longest increasing subsequence; And
An item sorting unit for sorting the items based on the update;
And an item sorting device for sorting the items. The method of claim 11,
The item group generating unit
Wherein the grouping of items in which the update order of the items included in the item list is incremented by 1 is performed. The method of claim 12,
The item update unit
An excluded group selection unit for selecting excluded groups corresponding to the longest incremental partial sequence among the item groups; And
And an update group selector for selecting the update groups by excluding the exclusion groups from the item groups. 14. The method of claim 13,
The exclusion group selector
And the item group corresponding to the start order included in the longest incremental partial sequence is selected as the exclusion groups. Alignment device. 15. The method of claim 14,
The exclusion group selector
And selects the exclusion groups considering the size of the group of the item groups corresponding to the start order included in the longest incremental partial sequence, when the longest incremental partial sequence is two or more. The method of claim 12,
The item update unit
And updates only the update items corresponding to the update groups among the items. 18. The method of claim 16,
The item arranging unit
And the item alignment is performed using multiple alignment indices. 18. The method of claim 17,
The item arranging unit
Wherein the item alignment is performed using an auxiliary index among the multiple sorting indexes for items having the same primary index among the multiple sorting indexes among the items. . 19. The method of claim 18,
The item update unit
And updates the update items in consideration of the multiple sorting indexes of the items whose update order is different one by one from the update items among the items. A computer-readable recording medium on which a program for executing the method according to any one of claims 1 to 10 is recorded.

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