CN115049333A - Book borrowing statistical management system and method - Google Patents
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Abstract
The invention provides a book borrowing statistical management system and a method thereof, wherein the system comprises: the information counting end is used for counting original book information and book borrowing information of a target library; the evolution analysis end is used for excavating a time sequence analysis result of the book active words corresponding to the target library based on the original book information, the book borrowing information and the latest determined excavation factor; the newly added determining end is used for determining a corresponding book prediction active word based on the time sequence analysis result and determining a corresponding newly added book list based on the book prediction active word; and the book management terminal is used for updating the existing book stock of the target library based on the newly added book list, obtaining a corresponding management result and updating a corresponding mining factor based on the management result. The forecasting excavation of the book borrowing requirement is realized by adopting the combination of time sequence analysis and information excavation technology, and further the management of the newly added stock of book borrowing statistics is realized.
Description
Technical Field
The invention relates to the technical field of book management, in particular to a book borrowing statistical management system and a book borrowing statistical management method.
Background
At present, the conventional library mostly adopts a manual counting or automatic counting method to realize the counting of the borrowing information, the library inventory is supplemented by the follow-up borrowing information analysis borrowing demand obtained by counting or the manual analysis market hotspot, however, the borrowing information manual analysis borrowing demand obtained by counting or the manual analysis market hotspot further determines the newly added inventory of the library, so that great errors can exist, a large amount of manual experience and demand insight can be needed, the newly added inventory can not accurately meet the actual borrowing demand, and a large amount of books are retained.
With the development of information technology, the existing information analysis technology has been greatly improved and is applied to a plurality of fields, but the existing book management technology field does not adopt the combination of time sequence analysis and information mining technology to realize the forecast mining of book borrowing requirements, which will bring new attempts and unexpected technical improvement to the book borrowing statistical management field.
Therefore, the invention provides a book borrowing statistical management system and a book borrowing statistical management method, which adopt the combination of time sequence analysis and information mining technology to realize the prediction mining of book borrowing requirements, and further realize the management of newly added inventory of book borrowing statistics.
Disclosure of Invention
The invention provides a book borrowing statistical management system and method, which are used for realizing the prediction and mining of book borrowing requirements by adopting the combination of time sequence analysis and information mining technology, reducing the prediction error of the borrowing requirements under the condition of not needing a large amount of manual experience and requirement insights, realizing that newly added inventory accurately meets the actual borrowing requirements, and further realizing the management of the newly added inventory of book borrowing statistics.
The invention provides a book borrowing statistical management system, which comprises:
the information counting end is used for counting original book information and book borrowing information of a target library;
the evolution analysis end is used for excavating a time sequence analysis result of the book active words corresponding to the target library based on the original book information, the book borrowing information and the latest determined excavation factor;
the newly added determining end is used for determining a corresponding book prediction active word based on the time sequence analysis result and determining a corresponding newly added book list based on the book prediction active word;
and the book management terminal is used for updating the existing book stock of the target library based on the newly added book list, obtaining a corresponding management result and updating a corresponding mining factor based on the management result.
Preferably, the book borrowing statistics management system comprises the information statistics terminal:
the original input module is used for inputting all book information contained in the initial inventory of the target library based on manual input or a radio frequency identification mode to obtain corresponding original book information;
the multi-terminal acquisition module is used for establishing a link relation with all the borrowing mode terminals and acquiring borrowing operation information obtained based on all the borrowing modes in real time based on the link relation;
and the sequencing integration module is used for sequencing and integrating the borrowing operation information obtained by all the borrowing modes to obtain corresponding book borrowing information.
Preferably, the book borrowing statistics management system further comprises a sorting integration module, wherein the sorting integration module comprises:
the information acquisition unit is used for acquiring the current inventory information in the target library in real time;
the information integration unit is used for sequencing, integrating and de-duplicating the borrowing operation information obtained in all the borrowing modes according to a time sequence to obtain corresponding complete borrowing information;
and the information correction unit is used for correcting the complete book borrowing information based on the current inventory information to obtain corresponding book borrowing information.
Preferably, the book borrowing statistical management system includes:
the first determining module is used for determining a first hot word co-occurrence network of each original book contained in the original book information;
the relation mining module is used for mining the hot word correlation relation among all the original books contained in the original book information based on the latest determined mining factor;
the related fusion module is used for constructing a corresponding hot word related fusion network based on the hot word related relationship and the first hot word co-occurrence network;
the second determining module is used for determining a second hot spot word co-occurrence network of each book to be borrowed, wherein the second hot spot words are contained in the book borrowing information;
the related association module is used for performing related association on the second hot word co-occurrence network of each book to be borrowed, contained in the book borrowing information corresponding to different moments, and the hot word related fusion network based on the latest determined mining factor to obtain the borrowing hot word fusion network corresponding to the moments;
the dynamic generation module is used for generating a corresponding dynamic borrowing hot word fusion network based on the corresponding borrowing hot word fusion networks at different moments;
and the time sequence analysis module is used for carrying out time sequence analysis on the dynamic borrowing hot word fusion network to obtain a time sequence analysis result of the book active words corresponding to the target library.
Preferably, the book borrowing statistic management system further comprises a time sequence analysis module, wherein the time sequence analysis module comprises:
the time selecting unit is used for selecting a plurality of analysis times on a time axis aligned with the dynamic borrowing hot word fusion network;
the system comprises a first determining unit, a first analyzing unit and a second determining unit, wherein the first determining unit is used for determining an analyzing hot word bag corresponding to a borrowing hot word fusion network corresponding to each analyzing moment and a first central correlation degree corresponding to each analyzing hot word contained in the analyzing hot word bag;
the word screening unit is used for screening out a first analysis hot spot word of which the first center correlation degree is greater than a center correlation degree threshold value in the analysis hot spot word bag;
the first construction unit is used for constructing a corresponding first hot spot word analysis network based on the correlation of the first analysis hot spot word in the corresponding borrowing hot spot word fusion network and the first analysis hot spot word;
a second determining unit, configured to determine a second central correlation degree of the first hot spot word in the first hot spot word analysis network;
a difference calculation unit for calculating a corresponding central correlation difference based on the first central correlation and the second central correlation;
a continuous screening unit, configured to determine whether the center correlation difference and the second center correlation are both positive numbers, if so, continuously screen the first analysis hot spot word based on the second center correlation and a forward gradient center correlation threshold list, until the center correlation difference and the second center correlation are both 0, then use the screened analysis hot spot word as a book active word at a corresponding analysis time, otherwise, continuously screen the first analysis hot spot word based on the second center correlation and a reverse gradient center correlation threshold list, until the center correlation difference and the second center correlation are both positive numbers, then continuously screen the first analysis hot spot word based on a newly determined center correlation and the forward gradient center correlation threshold list, until the center correlation difference and the second center correlation are both 0, taking the screened analysis hot words as book active words corresponding to the analysis moment;
the second construction unit is used for constructing book active word networks corresponding to different analysis moments based on the book active words corresponding to the corresponding analysis moments and the correlation relationship of the book active words in the corresponding borrowing hot word fusion network;
and the time sequence analysis unit is used for carrying out time sequence analysis on the book active word networks corresponding to different analysis moments to obtain a time sequence analysis result of the book active words corresponding to the target library.
Preferably, the book borrowing statistics management system further comprises a time sequence analysis unit, wherein the time sequence analysis unit comprises:
the word selection sub-unit is used for calculating the pointing weight of the corresponding book active word based on the correlation among the book active words contained in the book active word network, and taking the book active word corresponding to the maximum pointing weight as the most active word in the corresponding book active word network;
the first construction subunit is used for constructing a corresponding active word time sequence evolution path based on the position of the most active word in the corresponding book active word network;
the second calculation subunit is configured to calculate a first active evolution value between each most active word and a corresponding previous most active word in the active word time sequence evolution path and a second active evolution value between each most active word and a corresponding next most active word;
the word screening subunit is configured to screen the most active word based on the first active evolution value and the second active evolution value to obtain a corresponding representative most active word;
the second construction subunit is used for constructing a corresponding final time sequence evolution path based on the position of the representative most active word in the active word time sequence evolution path;
the system comprises a word bag determining subunit, a word bag determining unit and a word bag determining unit, wherein the word bag determining subunit is used for determining the correlation degree of each book active word in a corresponding book active word network and a corresponding most active word, and determining the related active word bag in the book active word network based on the correlation degree;
and the result binding subunit is used for binding the related hot word bag and the final time sequence evolution path to obtain a corresponding time sequence analysis result.
Preferably, the book borrowing statistical management system further comprises a newly added determining end:
the activity analysis module is used for predicting corresponding book prediction activity words based on the time sequence characteristics of the time sequence analysis result;
the hot spot mining module is used for acquiring a newly-added book list and determining a hot spot word bag of the newly-added books contained in the newly-added book list based on the newly-determined mining factor;
the correlation determination module is used for determining the correlation degree between the hot words contained in the hot word bag and the book prediction active words;
the fitting degree calculation module is used for calculating the corresponding hot point fitting degree based on the corresponding correlation degree of each hot point word contained in the hot point word bag corresponding to the newly-added book;
and the list determining module is used for determining a corresponding newly added book list based on the hot spot attaching degree.
Preferably, the book borrowing statistics management system further comprises a list determining module, wherein the list determining module comprises:
the book sorting unit is used for sorting all newly-added books according to the sequence of the hot spot attaching degrees from large to small to obtain corresponding hot spot attaching and sorting results;
a third determining unit, configured to determine a total number of types of newly added books corresponding to the newly added books based on the newly added total number and the newly added number corresponding to the newly added books;
a fourth determining unit, configured to determine a corresponding final new book type based on the total number of the new book types and the hot spot attaching and sorting result;
a fifth determining unit, configured to determine a newly added number of each newly added book based on the hot spot attaching degree corresponding to the final newly added book type and the newly added total number;
and the number summarizing unit is used for summarizing the newly added numbers of all the newly added book types into a list to obtain a corresponding newly added book list.
Preferably, the book borrowing statistical management system comprises the book management terminal:
the updating management module is used for updating the existing book stock of the target library based on the newly added book list to obtain a corresponding management result;
the latest acquisition module is used for acquiring latest book borrowing information and a latest newly added book list based on the management result;
and the mining updating module is used for updating the latest mining factor based on the latest book borrowing information and the latest newly added book list.
The invention provides a book borrowing statistical management method, which comprises the following steps:
s1: counting original book information and book borrowing information of a target library;
s2: mining a time sequence analysis result of a book active word corresponding to the target library based on the original book information, the book borrowing information and the latest determined mining factor;
s3: determining a corresponding book prediction active word based on the time sequence analysis result, and determining a corresponding newly added book list based on the book prediction active word;
s4: and updating the existing book stock of the target library based on the newly added book list to obtain a corresponding management result.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic diagram of a book borrowing statistics management system according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an information statistics terminal according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a sort integration module according to an embodiment of the present invention;
fig. 4 is a schematic diagram of an evolution analysis end according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a timing analysis module according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of a timing analysis unit according to an embodiment of the present invention;
FIG. 7 is a diagram illustrating an added deterministic end in an embodiment of the present invention;
FIG. 8 is a diagram illustrating a list determination module according to an embodiment of the present invention;
FIG. 9 is a diagram of a book management side according to an embodiment of the present invention;
FIG. 10 is a flow chart of a book borrowing statistics management method according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Example 1:
the invention provides a book borrowing statistical management system, which comprises:
the information counting end is used for counting original book information and book borrowing information of a target library;
the evolution analysis end is used for excavating a time sequence analysis result of the book active words corresponding to the target library based on the original book information, the book borrowing information and the latest determined excavation factor;
the newly added determining end is used for determining corresponding book prediction active words based on the time sequence analysis result and determining a corresponding newly added book list based on the book prediction active words;
and the book management terminal is used for updating the existing book stock of the target library based on the newly added book list, obtaining a corresponding management result and updating a corresponding mining factor based on the management result.
In this embodiment, the target library is a library managed by the book borrowing statistics management system.
In this embodiment, the original book information is the book information when all books in the target library are not borrowed.
In this embodiment, the book borrowing information is basic information of the books borrowed from the target library, such as book names, publishing centers, authors, and publishing dates and years.
In this embodiment, the mining factor is a factor for controlling the mining degree when mining the correlation between the original book information and the hot-spot words in the books included in the book borrowing information.
In this embodiment, the book active word is a hot word that is common to or has a high common rate in the books that are frequently borrowed.
In this embodiment, the time sequence analysis result is a result obtained by performing time sequence analysis on the active words of the book corresponding to the target library based on the original book information, the book borrowing information, and the latest determined mining factor.
In this embodiment, the book predicted active word is a hot word predicted based on the time sequence analysis result and frequently borrowed.
In this embodiment, the newly added book list is a book list that needs to be newly added in the target library and is determined based on the book prediction active words.
In this embodiment, the existing book inventory is the current book inventory of the target library.
In this embodiment, the management result is a result of managing the inventory and borrowing statistics of the target library, which is obtained after the existing library inventory of the target library is updated based on the newly added book list.
The beneficial effects of the above technology are: the book borrowing demand forecasting method has the advantages that the forecasting excavation of the book borrowing demand is realized by combining the time sequence analysis technology and the information mining technology, the error of the book borrowing demand forecasting is reduced under the condition that a large amount of manual experience and demand insights are not needed, the newly increased inventory is realized, the actual borrowing demand is accurately met, and the management of the newly increased inventory of book borrowing statistics is realized.
Example 2:
on the basis of the embodiment 1, the book borrowing statistics management system comprises an information statistics terminal and an information statistics terminal, wherein the information statistics terminal comprises:
the original input module is used for inputting all book information contained in the initial inventory of the target library based on manual input or a radio frequency identification mode to obtain corresponding original book information;
the multi-terminal acquisition module is used for establishing a link relation with all the borrowing mode terminals and acquiring borrowing operation information obtained based on all the borrowing modes in real time based on the link relation;
and the sequencing integration module is used for sequencing and integrating the borrowing operation information obtained by all the borrowing modes to obtain corresponding book borrowing information.
In this embodiment, the borrowing mode terminal is, for example: the system comprises a borrowing management official network, a borrowing management public number, a field borrowing management terminal and the like.
In this embodiment, the borrowing operation information is information related to the borrowing operation, which is obtained based on all the borrowing modes and is obtained in real time based on the link relationship.
The beneficial effects of the above technology are: the method comprises the steps of obtaining original book information corresponding to a target library based on manual input and radio frequency identification, obtaining book borrowing information of the target library in real time based on connection relations with all borrowing mode terminals, providing a data base for follow-up accurate analysis of borrowing requirements of audiences of the target library, improving intelligent and accurate management of book borrowing, and effectively avoiding errors of manual statistics and risks that books are possibly detained.
Example 3:
on the basis of embodiment 2, the book borrowing statistics management system comprises a sorting integration module and a library management module, wherein the sorting integration module comprises:
the information acquisition unit is used for acquiring current inventory information in the target library in real time;
the information integration unit is used for sequencing, integrating and de-duplicating the borrowing operation information obtained in all the borrowing modes according to a time sequence to obtain corresponding complete borrowing information;
and the information correction unit is used for correcting the complete borrowing information based on the current inventory information to obtain corresponding book borrowing information.
In this embodiment, the current inventory information is the current book inventory information of the target library.
In this embodiment, the complete borrowing information is the book borrowing information obtained by sequencing, integrating and de-duplicating the borrowing operation information obtained in all the borrowing modes according to the time sequence.
In this embodiment, the book borrowing information is the book borrowing information obtained after the complete borrowing information is corrected based on the current inventory information.
The beneficial effects of the above technology are: the borrowing operation information obtained by all the borrowing modes is sorted, integrated, deduplicated and corrected, and the accuracy of the obtained book borrowing information is ensured. In this embodiment, carry out the accurate sequencing to books information through the mode of intelligence, can ensure that every books information is all by accurate arrangement, deduplication and correction, effectively avoided a great deal of problems that artifical sequencing appears, promote books management's intellectuality greatly, reduce the cost of labor.
Example 4:
on the basis of embodiment 3, the book borrowing statistics management system includes:
the first determining module is used for determining a first hot word co-occurrence network of each original book contained in the original book information;
the relation mining module is used for mining the hot word correlation relation among all the original books contained in the original book information based on the latest determined mining factor;
the related fusion module is used for constructing a corresponding hot word related fusion network based on the hot word related relation and the first hot word co-occurrence network;
the second determining module is used for determining a second hot word co-occurrence network of each book to be borrowed contained in the book borrowing information;
the related association module is used for performing related association on the second hot word co-occurrence network of each book to be borrowed, contained in the book borrowing information corresponding to different moments, and the hot word related fusion network based on the latest determined mining factor to obtain the borrowing hot word fusion network corresponding to the moments;
the dynamic generation module is used for generating a corresponding dynamic borrowing hot word fusion network based on the corresponding borrowing hot word fusion networks at different moments;
and the time sequence analysis module is used for carrying out time sequence analysis on the dynamic borrowing hot word fusion network to obtain a time sequence analysis result of the book active words corresponding to the target library.
In this embodiment, the first hot word co-occurrence network is a network constructed based on a relationship that hot words included in each original book included in the original book information co-occur in the corresponding original book.
In this embodiment, the original book is a book included in the summary of the original book information.
In this embodiment, the hot word correlation is a corresponding mining degree set based on the newly determined mining factor, a corresponding mining correlation is determined based on the corresponding mining degree, and correlations between hot words included in all original books are mined based on the mining correlation.
In this embodiment, the hot word related fusion network is a network that performs fusion association on the first hot word co-occurrence network corresponding to each original book based on the hot word related relationship to obtain a network that represents the related relationship between the hot words included in all the original books.
In this embodiment, the second hot-spot word co-occurrence network is a network constructed by a relationship in which the hot-spot words included in each book to be borrowed included in the book borrowing information appear together in the corresponding book to be borrowed.
In this embodiment, the book to be borrowed is the book to be borrowed included in the book borrowing information.
In this embodiment, the borrowing hot-spot word fusion network is a fusion network that represents the correlation between all hot-spot words contained in the borrowing book at the corresponding time, obtained after the second hot-spot word co-occurrence network of each book contained in the book borrowing information corresponding to different times is correlated with the hot-spot word correlation fusion network, based on the latest determined mining factor.
In this embodiment, the dynamic borrowing hot word fusion network is a dynamic borrowing hot word fusion network generated by sequencing the corresponding borrowing hot word fusion networks at different times according to a time sequence.
In this embodiment, the book active words are hot words that are common to books frequently borrowed or have a high common rate.
The beneficial effects of the above technology are: by mining hot words contained in original books, mining the correlation between the hot words and mining the correlation between the hot words contained in the borrowed books, generating a corresponding borrowing hot word fusion network, generating a corresponding dynamic borrowing hot word fusion network based on the borrowing hot word fusion network at different moments generated by corresponding book borrowing information at different moments, and performing time sequence analysis on the dynamic borrowing hot word fusion network, the trend of book borrowing active words changing along with time can be analyzed, and the result of the time sequence analysis is an important basis for accurately analyzing the borrowing demand of target library audiences in the follow-up process.
Example 5:
on the basis of the embodiment 4, the book borrowing statistics management system comprises the timing analysis module and a library management module, wherein the timing analysis module comprises:
the time selecting unit is used for selecting a plurality of analysis times on a time axis aligned with the dynamic borrowing hot word fusion network;
the first determining unit is used for determining an analysis hot spot word bag corresponding to the borrowing hot spot word fusion network corresponding to each analysis moment and a first central relevance corresponding to each analysis hot spot word contained in the analysis hot spot word bag;
the word screening unit is used for screening out first analysis hot spot words with first central correlation degree larger than a central correlation degree threshold value in the analysis hot spot word bag;
the first construction unit is used for constructing a corresponding first hot spot word analysis network based on the correlation of the first analysis hot spot word in the corresponding borrowing hot spot word fusion network and the first analysis hot spot word;
a second determining unit, configured to determine a second central correlation degree of the first hot spot word in the first hot spot word analysis network;
a difference calculation unit for calculating a corresponding central correlation difference based on the first central correlation and the second central correlation;
a continuous screening unit, configured to determine whether the center correlation difference and the second center correlation are both positive numbers, if so, continuously screen the first analysis hot spot word based on the second center correlation and a forward gradient center correlation threshold list, until the center correlation difference and the second center correlation are both 0, then use the screened analysis hot spot word as a book active word at a corresponding analysis time, otherwise, continuously screen the first analysis hot spot word based on the second center correlation and a reverse gradient center correlation threshold list, until the center correlation difference and the second center correlation are both positive numbers, then continuously screen the first analysis hot spot word based on a newly determined center correlation and the forward gradient center correlation threshold list, until the center correlation difference and the second center correlation are both 0, taking the screened analysis hot words as book active words corresponding to the analysis moment;
the second construction unit is used for constructing book active word networks corresponding to different analysis moments based on the book active words corresponding to the corresponding analysis moments and the correlation relationship of the book active words in the corresponding borrowing hot word fusion network;
and the time sequence analysis unit is used for carrying out time sequence analysis on the book active word networks corresponding to different analysis moments to obtain a time sequence analysis result of the book active words corresponding to the target library.
In this embodiment, the analysis time is a plurality of times selected according to a preset period on a time axis aligned with the dynamic borrowing hot word fusion network.
In this embodiment, determining an analysis hot word bag corresponding to the borrowing hot word fusion network corresponding to each analysis time and a first central relevance corresponding to each analysis hot word contained in the analysis hot word bag includes:
and taking the mean value of the degree centrality value, the mesocentrality value and the approximate centrality value of the hot spot word in the corresponding borrowing hot spot word fusion network as the corresponding first central correlation degree.
In this embodiment, the analysis hot word bag is a hot word included in the borrowing hot word fusion network at the corresponding analysis time.
In this embodiment, the first central correlation degree is a numerical value representing the centrality of the analysis hot word in the corresponding borrowing hot word fusion network.
In this embodiment, the analysis hot word is a hot word contained in the analysis hot word bag.
In this embodiment, the first analysis hot spot word is an analysis hot spot word screened out in the analysis hot spot word bag that the first central relevance is greater than the central relevance threshold.
In this embodiment, the central correlation threshold is the minimum central correlation corresponding to the analysis hot word screened as the first analysis hot word.
In this embodiment, the first hot spot word analysis network is a hot spot word network generated after the correlation between the first analysis hot spot words and all the first analysis hot spot words included in the borrowed hot spot word fusion network is retained.
In this embodiment, the second central correlation is a numerical value representing the centrality of the first analysis hot spot word in the first hot spot word analysis network, that is, the centrality value, the mesocentrality value, and the average value close to the centrality value of the first analysis hot spot word in the first hot spot word analysis network are used as the corresponding second central correlation.
In this embodiment, a corresponding central correlation difference is calculated based on the first central correlation and the second central correlation, that is: and taking the difference value of the second central correlation degree and the second central correlation degree as the corresponding central correlation degree difference value.
In this embodiment, the list of the correlation thresholds of the center of the forward gradient is a list including the correlation thresholds of the center that are sequentially increased.
In this embodiment, the list of inverse gradient center correlation thresholds is a list including sequentially decreasing center correlation thresholds.
In this embodiment, the book active word network is a network formed by book active words corresponding to the analysis time, which are obtained after the correlation between the book active words and the book active words included in the borrowing hot word fusion network corresponding to the analysis time is retained.
The beneficial effects of the above technology are: the method comprises the steps that the centrality correlation, the forward gradient center correlation threshold value list and the reverse gradient center correlation threshold value list corresponding to each analysis hot word are determined based on the analysis hot words contained in the borrowing hot word fusion network and the correlation between the analysis hot words, the analysis hot words contained in the borrowing hot word fusion network are continuously screened, then the hot words capable of representing book content centers are screened, and the first step is laid for accurately predicting book borrowing requirements.
Example 6:
on the basis of embodiment 5, the book borrowing statistics management system comprises the timing analysis unit, and the timing analysis unit comprises:
the word selection sub-unit is used for calculating the pointing weight of the corresponding book active word based on the correlation among the book active words contained in the book active word network, and taking the book active word corresponding to the maximum pointing weight as the most active word in the corresponding book active word network;
the first construction subunit is used for constructing a corresponding active word time sequence evolution path based on the position of the most active word in the corresponding book active word network;
the second calculation subunit is configured to calculate a first active evolution value between each most active word and a corresponding previous most active word in the active word time sequence evolution path and a second active evolution value between each most active word and a corresponding next most active word;
the word screening subunit is configured to screen the most active word based on the first active evolution value and the second active evolution value to obtain a corresponding representative most active word;
the second constructing subunit is used for constructing a corresponding final time sequence evolution path based on the position of the representative most active word in the active word time sequence evolution path;
the word bag determining subunit is used for determining the correlation degree of each book active word in the corresponding book active word network and the corresponding most active word and determining the related active word bag in the book active word network based on the correlation degree;
and the result binding subunit is used for binding the related hot word bag and the final time sequence evolution path to obtain a corresponding time sequence analysis result.
In this embodiment, calculating the pointing weight of the active book word based on the correlation between the active book words included in the active book word network includes:
wherein ε is the directional weight of active words in the book, S point For the total number of other book active words in the corresponding book active word network, S all The total number of the book active words contained in the corresponding book active word network;
for example, S point Is 5, S all If it is 100, ε is 0.05.
In this embodiment, the most active word is the book active word corresponding to the maximum pointing weight in the corresponding book active word network.
In this embodiment, the active word time sequence evolution path is a path constructed by connecting the positions of the most active words in the corresponding book active word network according to the positions on the time axis at the corresponding different analysis times.
In this embodiment, calculating a first active evolution value between each most active word and a corresponding previous most active word and a second active evolution value between each most active word and a corresponding next most active word in the active word time sequence evolution path includes:
in the formula,. DELTA. 1 Is the first active evolution value, Δ 2 Is the second active evolution value, d 1 For the distance between the currently calculated most active word and the corresponding previous most active word in the active word time sequence evolution path, d 2 For the distance between the currently calculated most active word and the corresponding next most active word in the active word time sequence evolution path, d max For the maximum distance between the book active word contained in the corresponding book active word network and the currently calculated most active word, d min The minimum distance between the book active word contained in the corresponding book active word network and the most active word calculated currently is S point For the total number of other book active words in the corresponding book active word network, S all For the total number of book active words contained in the corresponding book active word network, S 1point The total number of other book active words in the corresponding book active word network which have a correlation with the corresponding previous most active word, S 2point The total number of other book active words which have a correlation with the corresponding last active word in the corresponding book active word network;
e.g. d 1 Is 10, d 2 Is 15, d max Is 55, d min Is 5, S point Is 5, S all Is 100, S 1point Is 10, S 2point Is 10, then Δ 1 Is 0.15, Δ 2 Is 0.28.
In this embodiment, the representative most active word is the most active word corresponding to the largest sum of the first active evolution value and the corresponding second active evolution value.
In this embodiment, the final time sequence evolution path is a path constructed by connecting positions of the most active word in the active word time sequence evolution path according to positions on the time axis corresponding to different analysis times.
In this embodiment, determining the degree of correlation between each book active word in the corresponding book active word network and the corresponding most active word includes:
the ratio of the total number of the book active words separated from the corresponding most active words in the corresponding book active word network to the total number of the book active words contained in the corresponding book active word network is obtained.
In this embodiment, the related active word bag is a word bag formed by active words of the book whose relevance satisfies the relevance threshold.
The beneficial effects of the above technology are: and screening out the most active representative word in the corresponding book active word network based on the corresponding pointing weight of the book active word and the corresponding active evolution value, and obtaining a corresponding time sequence analysis result based on the most active representative word and the correlation degree of each book active word in the corresponding book active word network and the corresponding most active word, so as to further lay the foundation for accurately predicting the book borrowing demand.
Example 7:
on the basis of embodiment 6, the book borrowing statistical management system includes:
the activity analysis module is used for predicting corresponding book prediction activity words based on the time sequence characteristics of the time sequence analysis result;
the hot spot mining module is used for acquiring a newly-added book list and determining a hot spot word bag of the newly-added books contained in the newly-added book list based on the newly-determined mining factor;
the correlation determination module is used for determining the correlation degree between the hot words contained in the hot word bag and the book prediction active words;
the fitting degree calculation module is used for calculating the corresponding hot point fitting degree based on the corresponding correlation degree of each hot point word contained in the hot point word bag corresponding to the newly-added book;
and the list determining module is used for determining a corresponding newly added book list based on the hot spot attaching degree.
In this embodiment, the time sequence feature is a feature of the book active word changing with time in the time sequence analysis result.
In this embodiment, the book prediction active word is a hot word in the book to be frequently borrowed, which is predicted based on the time sequence characteristics of the time sequence analysis result.
In this embodiment, the list of newly-added books is a list of available books that can be added to the target library.
In this embodiment, the hot word bag is a word bag formed by hot words contained in newly-added books contained in the newly-added book list determined based on the newly-determined mining factor.
In this embodiment, the newly added book is a book included in the newly added book list.
In this embodiment, determining the correlation between the hot words contained in the hot word bag and the book predicted active words includes:
the method comprises the steps of extracting the correlation between the hot words contained in the hot word bag and book predicted active words, constructing a corresponding correlation network based on the correlation, and determining the ratio of the total number of hot words separated between the hot words and the book predicted active words in the correlation network to the hot words contained in the hot word bag.
In this embodiment, calculating a corresponding hot spot attaching degree based on a correlation degree corresponding to each hot spot word included in the hot spot word bag corresponding to the newly added book includes:
and taking the ratio of the correlation degree of the corresponding hot word to the sum of the correlation degrees corresponding to all the hot words contained in the hot word bag as the corresponding hot word attaching degree.
The beneficial effects of the above technology are: and predicting corresponding book prediction active words based on the time sequence analysis result, screening the newly added books of the target library based on the hot spot attaching degree between the book prediction active words and the hot spot words contained in the newly added books, and accurately determining newly added stock meeting the borrowing requirements of the target library audiences.
Example 8:
on the basis of embodiment 7, the book borrowing statistics management system comprises:
the book sorting unit is used for sorting all newly-added books according to the sequence of the hot spot attaching degrees from large to small to obtain corresponding hot spot attaching and sorting results;
a third determining unit, configured to determine a total number of types of newly added books corresponding to the newly added books based on the newly added total number and the newly added number corresponding to the newly added books;
a fourth determining unit, configured to determine a corresponding final newly added book type based on the total number of the newly added book types and the hot spot attaching and sorting result;
a fifth determining unit, configured to determine a new number of each newly added book based on the hot spot attaching degree corresponding to the final newly added book type and the newly added total number;
and the number summarizing unit is used for summarizing the newly added numbers of all the newly added book types into a list to obtain a corresponding newly added book list.
In this embodiment, the hot spot attaching sorting result is a result obtained by sorting all newly-added books in a descending order based on the hot spot attaching degrees.
In this embodiment, determining the total number of the types of newly added books based on the total number of newly added books and the newly added number corresponding to the newly added books includes: and taking the quotient between the newly increased total number and the minimum newly increased number as the corresponding newly increased book category total number.
In this embodiment, the newly added book types are the total number of newly added books in the previous newly added book types in the hot spot attaching and sorting result.
In this embodiment, determining the newly added number of each newly added book based on the hot spot attaching degree corresponding to the finally added book type and the newly added total number includes:
and taking the product of the ratio of the corresponding hotspot attaching degree to the sum of all hotspot attaching degrees and the newly-added total number as the newly-added number of the newly-added books of the corresponding category.
The beneficial effects of the above technology are: and sequencing and screening all newly added books based on the hot spot attaching degree so as to accurately determine the newly added book information of the target library.
Example 9:
on the basis of the embodiment 8, the book borrowing statistic management system comprises:
the updating management module is used for updating the existing book stock of the target library based on the newly added book list to obtain a corresponding management result;
the latest acquisition module is used for acquiring latest book borrowing information and a latest newly added book list based on the management result;
and the mining updating module is used for updating the latest mining factor based on the latest book borrowing information and the latest newly added book list.
In this embodiment, updating the latest mining factor based on the latest book borrowing information and the latest newly added book list is that:
and determining the number of books borrowed from all the newly added books in a preset period based on the newly determined book borrowing information, calculating the ratio between the number of the borrowed books and all the newly added books, and taking the product of the calculated ratio and the corresponding mining factor as a new mining factor.
The beneficial effects of the above technology are: the existing library in the target library is managed based on the newly added book list, the latest mining factor is updated based on the latest book borrowing information and the latest newly added book list, and continuous optimization of the mining process of borrowing requirements of audiences of the target library is achieved.
Example 10:
the invention provides a book borrowing statistical management method, which comprises the following steps:
s1: counting original book information and book borrowing information of a target library;
s2: mining a time sequence analysis result of a book active word corresponding to the target library based on the original book information, the book borrowing information and the latest determined mining factor;
s3: determining a corresponding book prediction active word based on the time sequence analysis result, and determining a corresponding newly added book list based on the book prediction active word;
s4: and updating the existing book stock of the target library based on the newly added book list to obtain a corresponding management result.
The beneficial effects of the above technology are: the book borrowing demand forecasting method has the advantages that the forecasting excavation of the book borrowing demand is realized by combining the time sequence analysis technology and the information mining technology, the error of the book borrowing demand forecasting is reduced under the condition that a large amount of manual experience and demand insights are not needed, the newly increased inventory is realized, the actual borrowing demand is accurately met, and the management of the newly increased inventory of book borrowing statistics is realized.
According to the invention, the forecasting excavation of the book borrowing demand is realized by adopting the combination of the time sequence analysis and the information excavation technology, so that the management of newly added stock of book borrowing statistics is realized, the intellectualization, the accuracy and the predictability are improved, and the labor cost is reduced.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A book borrowing statistics management system, characterized by comprising:
the information counting end is used for counting original book information and book borrowing information of a target library;
the evolution analysis end is used for excavating a time sequence analysis result of the book active words corresponding to the target library based on the original book information, the book borrowing information and the latest determined excavation factor;
the newly added determining end is used for determining a corresponding book prediction active word based on the time sequence analysis result and determining a corresponding newly added book list based on the book prediction active word;
and the book management terminal is used for updating the existing book stock of the target library based on the newly added book list, obtaining a corresponding management result and updating a corresponding mining factor based on the management result.
2. The book borrowing statistical management system according to claim 1, wherein the information statistics terminal comprises:
the original input module is used for inputting all book information contained in the initial inventory of the target library based on manual input or a radio frequency identification mode to obtain corresponding original book information;
the multi-terminal acquisition module is used for establishing a link relation with all the borrowing mode terminals and acquiring borrowing operation information obtained based on all the borrowing modes in real time based on the link relation;
and the sequencing integration module is used for sequencing and integrating the borrowing operation information obtained by all the borrowing modes to obtain corresponding book borrowing information.
3. The book borrowing statistics management system according to claim 2, wherein the ranking integration module comprises:
the information acquisition unit is used for acquiring the current inventory information in the target library in real time;
the information integration unit is used for sequencing, integrating and de-duplicating the borrowing operation information obtained in all the borrowing modes according to a time sequence to obtain corresponding complete borrowing information;
and the information correction unit is used for correcting the complete borrowing information based on the current inventory information to obtain corresponding book borrowing information.
4. The book borrowing statistical management system according to claim 1, wherein the evolution analysis terminal comprises:
the first determining module is used for determining a first hot word co-occurrence network of each original book contained in the original book information;
the relation mining module is used for mining the hot word correlation relation among all the original books contained in the original book information based on the latest determined mining factor;
the related fusion module is used for constructing a corresponding hot word related fusion network based on the hot word related relation and the first hot word co-occurrence network;
the second determining module is used for determining a second hot word co-occurrence network of each book to be borrowed contained in the book borrowing information;
the relevant association module is used for carrying out relevant association on a second hot word co-occurrence network of each book to be borrowed, which is contained in book borrowing information corresponding to different moments, and the hot word relevant fusion network based on the newly determined mining factor to obtain a borrowing hot word fusion network corresponding to the moments;
the dynamic generation module is used for generating a corresponding dynamic borrowing hot word fusion network based on the corresponding borrowing hot word fusion networks at different moments;
and the time sequence analysis module is used for carrying out time sequence analysis on the dynamic borrowing hot word fusion network to obtain a time sequence analysis result of the book active words corresponding to the target library.
5. The book borrowing statistics management system according to claim 4, wherein the timing analysis module comprises:
the time selecting unit is used for selecting a plurality of analysis times on a time axis aligned with the dynamic borrowing hot word fusion network;
the system comprises a first determining unit, a first analyzing unit and a second determining unit, wherein the first determining unit is used for determining an analyzing hot word bag corresponding to a borrowing hot word fusion network corresponding to each analyzing moment and a first central correlation degree corresponding to each analyzing hot word contained in the analyzing hot word bag;
the word screening unit is used for screening out first analysis hot spot words with first central correlation degree larger than a central correlation degree threshold value in the analysis hot spot word bag;
the first construction unit is used for constructing a corresponding first hot spot word analysis network based on the correlation of the first analysis hot spot word in the corresponding borrowing hot spot word fusion network and the first analysis hot spot word;
a second determining unit, configured to determine a second central correlation degree of the first hot spot word in the first hot spot word analysis network;
a difference calculation unit for calculating a corresponding central correlation difference based on the first central correlation and the second central correlation;
a continuous screening unit, configured to determine whether the center correlation difference and the second center correlation are both positive numbers, if so, continuously screen the first analysis hot spot word based on the second center correlation and a forward gradient center correlation threshold list, until the center correlation difference and the second center correlation are both 0, then use the screened analysis hot spot word as a book active word at a corresponding analysis time, otherwise, continuously screen the first analysis hot spot word based on the second center correlation and a reverse gradient center correlation threshold list, until the center correlation difference and the second center correlation are both positive numbers, then continuously screen the first analysis hot spot word based on a newly determined center correlation and the forward gradient center correlation threshold list, until the center correlation difference and the second center correlation are both 0, taking the screened analysis hot words as book active words corresponding to the analysis moment;
the second construction unit is used for constructing book active word networks corresponding to different analysis moments based on the book active words corresponding to the corresponding analysis moments and the correlation relationship of the book active words in the corresponding borrowing hot word fusion network;
and the time sequence analysis unit is used for carrying out time sequence analysis on the book active word networks corresponding to different analysis moments to obtain a time sequence analysis result of the book active words corresponding to the target library.
6. The book borrowing statistics management system according to claim 5, wherein the timing analysis unit comprises:
the word selection sub-unit is used for calculating the pointing weight of the corresponding book active word based on the correlation among the book active words contained in the book active word network, and taking the book active word corresponding to the maximum pointing weight as the most active word in the corresponding book active word network;
the first constructing subunit is used for constructing a corresponding active word time sequence evolution path based on the position of the most active word in the corresponding book active word network;
the second calculation subunit is configured to calculate a first active evolution value between each most active word and a corresponding previous most active word in the active word time sequence evolution path and a second active evolution value between each most active word and a corresponding next most active word;
the word screening subunit is configured to screen the most active word based on the first active evolution value and the second active evolution value to obtain a corresponding representative most active word;
the second construction subunit is used for constructing a corresponding final time sequence evolution path based on the position of the representative most active word in the active word time sequence evolution path;
the word bag determining subunit is used for determining the correlation degree of each book active word in the corresponding book active word network and the corresponding most active word and determining the related active word bag in the book active word network based on the correlation degree;
and the result binding subunit is used for binding the related hot word bag and the final time sequence evolution path to obtain a corresponding time sequence analysis result.
7. The book borrowing statistics management system according to claim 1, wherein the newly added determination terminal comprises:
the activity analysis module is used for predicting corresponding book prediction activity words based on the time sequence characteristics of the time sequence analysis result;
the hot spot mining module is used for acquiring a newly-added book list and determining a hot spot word bag of the newly-added books contained in the newly-added book list based on the newly-determined mining factor;
the correlation determination module is used for determining the correlation degree between the hot words contained in the hot word bag and the book prediction active words;
the fitting degree calculation module is used for calculating the corresponding hot point fitting degree based on the corresponding correlation degree of each hot point word contained in the hot point word bag corresponding to the newly-added book;
and the list determining module is used for determining a corresponding newly added book list based on the hot spot attaching degree.
8. The book borrowing statistics management system according to claim 7, wherein the list determining module comprises:
the book sorting unit is used for sorting all newly-added books based on the sequence of the hot spot attaching degrees from large to small to obtain corresponding hot spot attaching sorting results;
a third determining unit, configured to determine a total number of types of the newly added books based on the newly added total number and the newly added number corresponding to the newly added books;
a fourth determining unit, configured to determine a corresponding final new book type based on the total number of the new book types and the hot spot attaching and sorting result;
a fifth determining unit, configured to determine a new number of each newly added book based on the hot spot attaching degree corresponding to the final newly added book type and the newly added total number;
and the number summarizing unit is used for summarizing the newly added numbers of all the newly added book types into a list to obtain a corresponding newly added book list.
9. The book borrowing statistic management system according to claim 1, wherein the book management terminal comprises:
the updating management module is used for updating the existing book stock of the target library based on the newly added book list to obtain a corresponding management result;
the latest acquisition module is used for acquiring latest book borrowing information and a latest newly added book list based on the management result;
and the mining updating module is used for updating the latest mining factor based on the latest book borrowing information and the latest newly added book list.
10. A book borrowing statistical management method is characterized by comprising the following steps:
s1: counting original book information and book borrowing information of a target library;
s2: excavating a time sequence analysis result of a book active word corresponding to the target library based on the original book information, the book borrowing information and the latest determined excavation factor;
s3: determining a corresponding book prediction active word based on the time sequence analysis result, and determining a corresponding newly added book list based on the book prediction active word;
s4: and updating the existing book stock of the target library based on the newly added book list to obtain a corresponding management result.
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