CN113392204A - Financial information retrieval system based on block chain - Google Patents
Financial information retrieval system based on block chain Download PDFInfo
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Abstract
The invention discloses a financial information retrieval system based on a block chain, which belongs to the field of information retrieval and solves the problem that a mode for calculating various vocabularies is not arranged in the system, and by the mode, better fit between retrieved documents and the retrieved vocabularies can be ensured, a data segmentation processing module extracts symbols, expressions and language aids in the financial information to obtain a word segment mean value CDi through calculation, the word segment mean value CDi is calculated by adopting the same formula for the documents obtained through retrieval, a mean matching module matches the mean values through mean matching, a similar document retrieval module can extract similar documents with the word segment mean values, a mean matching module matches the calculated CDi and sends the matching degree to the document retrieval module, a document extraction module extracts system documents in the cloud of the block chain and finishes extraction, the output module outputs the extracted documents, so that an operator can extract document data corresponding to the retrieval.
Description
Technical Field
The invention belongs to the field of information retrieval, and particularly relates to a financial information retrieval system based on a block chain.
Background
The blockchain is a term in the field of information technology, and essentially, the blockchain is a shared database, data or information stored in the shared database lays a solid 'trust' foundation, creates a reliable 'cooperation' mechanism, and has a wide application prospect.
The invention with the patent publication number of CN106682174B is specifically a short text information retrieval system based on big data application, which comprises a classification acquisition system and a short text preprocessing module, wherein the output end of the classification acquisition system is connected with the input end of a word segment preprocessing module in a signal way, the word segments output by the word segment preprocessing module are processed by a word segment splitting module and a word segment diversity module in sequence, and then the data of a split word association set is transmitted to a shared database, the invention has reasonable functional design, the retrieval word segments are counted and processed on the basis of the big data, when the short text information retrieval is carried out, the short text is reasonably split and combined, the word frequency is obtained by reversely pushing the word segments, the information output is carried out by the size of the word frequency, the burden of the retrieval system is greatly simplified, the rapid comparison is realized, and the timeliness of the information retrieval can be improved under the real-time updating state of the big data, and avoids missing retrieval of data.
In the using process of the system, only word segments are preprocessed, documents with similar word segments are extracted, the extracting mode possibly causes the content in the documents to be inconsistent with the content to be searched, the accuracy is not high, a mode for calculating various vocabularies is not arranged in the system, and the searched documents and the searched vocabularies can be better fit through the mode.
Disclosure of Invention
In order to solve the problems of the scheme, the invention provides a financial information retrieval system based on a block chain.
The purpose of the invention can be realized by the following technical scheme: a financial information retrieval system based on a block chain comprises a data acquisition module, a data classification module, a data matching module, a split word partitioning module, a data segmentation processing module, a block chain cloud, a similar document retrieval module, a mean matching module, a document extraction module and an output module;
the data acquisition module is used for acquiring and processing the input financial information and transmitting the acquired data into the data classification module;
the data classification module is used for classifying various data and classifying classification information including keywords of various industries;
the split word partitioning module is used for splitting data vocabularies and partitioning the split keywords;
and the data segmentation processing module segments various data, extracts and calculates other words and phrases, and calculates a financial information retrieval value.
Preferably, the data segmentation processing module comprises the following processing steps:
the method comprises the following steps that firstly, a data segmentation processing module extracts symbols, expressions and language aids in financial information, the number of occurrences of the symbols is recorded as F, and the number of occurrences of the expressions and the language aids is recorded as B and Y;
secondly, the data segmentation processing module marks the main split words subjected to partitioning and records the occurrence frequency of the split words as C;
step three, adopting a formula
Calculating to obtain a word segment mean value CDi, wherein A1, A2, A3 and A4 are all preset coefficient factors, and A1 is more than A2 is more than A3 is more than A4 is more than 0;
and step four, calculating the word segment mean value CDi of the searched documents by adopting the same formula, matching the mean value by the mean value matching module, and extracting similar documents.
Preferably, a large amount of cloud documents are contained in the cloud end of the block chain and are used for retrieval and extraction by an operator.
Preferably, the similar document retrieval module can extract similar documents of the word segment mean value, the mean value matching module can match the calculated CDi, the matching coincidence degree is sent to the document extraction module, the document extraction module extracts the system documents in the cloud of the block chain, and after extraction is completed, the output module outputs the extracted documents, so that an operator can extract document data corresponding to retrieval.
Preferably, the overlap ratio calculation method of the mean matching pair module is to compare the original word segment mean value CDi with the CDi of the document inside the block chain cloud, and the closer the comparison value is to 1, the more similar the document represents the similarity between the document and the corresponding search document.
Preferably, the similar document retrieval module extracts documents with contrast values within a range of 0.8-0.9 by receiving data information inside the mean matching module, and marks the documents as similar documents.
Preferably, the data segmentation processing module needs to divide the split word before processing, determine which region the split word belongs to, and search and extract documents with the same split word in the block chain cloud.
Preferably, the data matching module is used for extracting and matching the internal data of the block chain cloud and transmitting the matched data to the splitting word partitioning module.
Compared with the prior art, the invention has the beneficial effects that:
the data segmentation processing module extracts symbols, expressions and language help in financial information to obtain a word segment mean value CDi through calculation, the word segment mean value CDi is calculated for documents obtained through retrieval by adopting the same formula, the mean value is matched through the mean matching module, similar documents are extracted, the similar document retrieval module can extract the similar documents in the word segment mean value, the mean matching module can match the CDi obtained through calculation and sends the matching degree to the document extraction module, the document extraction module extracts the system documents in the cloud end of the block chain, and after extraction is completed, the output module outputs the extracted documents to enable operators to extract document data corresponding to retrieval;
the coincidence degree calculation mode of the mean matching pair module is that the original word segment mean value CDi is compared with the CDi of the document in the cloud of the block chain, the closer the comparison value is to 1, the more similar the document is represented to the corresponding retrieval document, the similar document retrieval module extracts the document with the comparison value within the range of 0.8-0.9 by receiving the data information in the mean matching pair module, the document is marked as the similar document, the similar document can be output to the outside through the output module, and an operator can look over the document to obtain the corresponding data, so that the good document retrieval effect is achieved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, a financial information retrieval system based on a block chain includes a data acquisition module, a data classification module, a data matching module, a split term partitioning module, a data segmentation processing module, a block chain cloud, a similar document retrieval module, a mean matching module, a document extraction module, and an output module;
the system comprises a data acquisition module, a data classification module, a data matching module, a split word partitioning module and a data segmentation processing module, wherein the data acquisition module, the data classification module, the data matching module, the split word partitioning module and the data segmentation processing module are in one-way connection from top to bottom from an output end to an input end;
the system comprises a similar document retrieval module, a document extraction module, an output module, a document matching module and an output module, wherein the similar document retrieval module is in bidirectional connection with a block chain cloud, the average matching module and the document extraction module are in bidirectional connection with the block chain cloud, the average matching module is respectively electrically connected with input ends of the document extraction module and the similar document retrieval module, the document extraction module is electrically connected with the output module, the output module is in wireless connection with an external display terminal, and the external display terminal can display a file output by the output module;
the data acquisition module is used for acquiring and processing the input financial information and transmitting the acquired data into the data classification module, and the acquired financial information is directed at retrieval information input into the retrieval system by an operator;
the data classification module is used for classifying various data and classifying classification information including keywords of various industries;
the splitting word partitioning module is used for splitting data vocabularies and partitioning split keywords, and the partitioning is convenient for matching with regional data inside the cloud end of the block chain and searching documents;
the data segmentation processing module segments various data, extracts and calculates other words, calculates a financial information retrieval value, and compares numerical values to ensure that the retrieved documents conform to documents required to be obtained by operators.
The data segmentation processing module comprises the following processing steps:
the method comprises the following steps that firstly, a data segmentation processing module extracts symbols, expressions and language aids in financial information, the number of occurrences of the symbols is recorded as F, and the number of occurrences of the expressions and the language aids is recorded as B and Y;
secondly, the data segmentation processing module marks the main split words subjected to partitioning and records the occurrence frequency of the split words as C;
step three, adopting a formula
Calculating to obtain a word segment mean value CDi, wherein A1, A2, A3 and A4 are all preset coefficient factors, and A1 is more than A2 is more than A3 is more than A4 is more than 0;
and step four, calculating the word segment mean value CDi of the searched documents by adopting the same formula, matching the mean value by the mean value matching module, and extracting similar documents.
The cloud storage system comprises a block chain cloud end, wherein a large number of cloud documents are contained in the block chain cloud end and are used for an operator to retrieve and extract, and the operator can also convey the documents to the inside of the block chain cloud end to store the documents.
The similar document retrieval module can extract similar documents of word segment mean values, the mean value matching module can match the CDi obtained through calculation, the matching coincidence degree is sent to the document extraction module, the document extraction module extracts system documents in the cloud end of the block chain, and after extraction is completed, the output module outputs the extracted documents to enable an operator to extract document data corresponding to retrieval.
The coincidence degree calculation mode of the mean matching module is that the original word segment mean value CDi is compared with the CDi of the document in the block chain cloud end, the closer the comparison value is to 1, the more similar the document is represented to the corresponding retrieval document, wherein the comparison mode is that the original word segment mean value CDi is divided by the CDi of the document in the block chain cloud end to obtain the comparison value, and the comparison value is less than or equal to 1.
The similar document retrieval module extracts documents with the contrast values within the interval of 0.8-0.9 by receiving data information in the mean matching module, records the documents as similar documents, and outputs the similar documents to the outside through the output module, so that an operator can browse the documents to obtain corresponding data.
Before processing, the data segmentation processing module needs to divide the split words, determine which region the split words belong to, search and extract documents with the same split words in the block chain cloud, and then calculate a mean value of the extracted application documents.
The data matching module is used for extracting and matching the internal data of the block chain cloud, transmitting the matched data to the splitting word partitioning module, and splitting the input fragment by the splitting word partitioning module.
The above formulas are all calculated by removing dimensions and taking numerical values thereof, the formula is a formula which is obtained by acquiring a large amount of data and performing software simulation to obtain the closest real situation, and the preset parameters and the preset threshold value in the formula are set by the technical personnel in the field according to the actual situation or obtained by simulating a large amount of data.
The working principle of the invention is as follows:
the data segmentation processing module extracts symbols, expressions and language aids in the financial information, and records the occurrence frequency of the symbols as F and the occurrence frequency of the expressions and the language aids as B and Y; the data segmentation processing module marks the main split words subjected to partitioning, records the split words as Ci, wherein i is the occurrence frequency of the split words, and calculates to obtain a word segment mean value CDi; calculating a word segment mean value CDi by adopting the same formula for the searched documents, matching the mean value through a mean matching module, extracting similar documents of the word segment mean value through a similar document searching module, matching the calculated CDi through a mean matching module, sending the matching coincidence degree into a document extracting module, extracting system documents in the cloud of the block chain through the document extracting module, and outputting the extracted documents through an output module after extraction is completed so that an operator can extract corresponding searched document data;
the coincidence degree calculation mode of the mean matching pair module is that the original word segment mean value CDi is compared with the CDi of the document in the block chain cloud end, the comparison value is closer to 1, the document is more similar to the corresponding retrieval document, the comparison mode is that the original word segment mean value CDi is divided by the CDi of the document in the block chain cloud end to obtain the comparison value, the comparison value is smaller than or equal to 1, the similar document retrieval module extracts the document with the comparison value within the range of 0.8-0.9 by receiving the data information in the mean matching pair module, the document is marked as the similar document, the similar document can be output to the outside through the output module, an operator can browse and check the document to obtain the corresponding data, and the good document retrieval effect is achieved.
The similar document retrieval module can extract similar documents of word segment mean values, the mean value matching module can match the CDi obtained through calculation, the matching coincidence degree is sent to the document extraction module, the document extraction module extracts system documents in the cloud end of the block chain, and after extraction is completed, the output module outputs the extracted documents to enable an operator to extract document data corresponding to retrieval.
In the embodiments provided by the present invention, it should be understood that the disclosed apparatus, device and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a module may be divided into only one logical function, and another division may be implemented in practice; modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the method of the embodiment.
It will also be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above examples are only intended to illustrate the technical process of the present invention and not to limit the same, and although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical process of the present invention without departing from the spirit and scope of the technical process of the present invention.
Claims (7)
1. A financial information retrieval system based on a block chain is characterized by comprising a data acquisition module, a data classification module, a data matching module, a split word partitioning module, a data segmentation processing module, a block chain cloud end, a similar document retrieval module, a mean value matching module, a document extraction module and an output module;
the data acquisition module is used for acquiring and processing the input financial information and transmitting the acquired data into the data classification module;
the data classification module is used for classifying various data and classifying classification information including keywords of various industries;
the split word partitioning module is used for splitting data vocabularies and partitioning the split keywords;
the data segmentation processing module segments various data, extracts and calculates other words and phrases, and calculates a financial information retrieval value;
the system comprises a similar document retrieval module, a mean matching module, a block chain cloud end and an output module, wherein the similar document retrieval module is used for extracting similar documents of word segment means, the mean matching module can match calculated values, data cloud documents are contained in the block chain cloud end and are used for retrieval and extraction by operators, the document extraction module is used for extracting document data in the block chain cloud end, and the output module outputs the document data to the outside;
the system comprises a data acquisition module, a data classification module, a data matching module, a split word partitioning module and a data segmentation processing module, wherein the data acquisition module, the data classification module, the data matching module, the split word partitioning module and the data segmentation processing module are in one-way connection from top to bottom from an output end to an input end;
wherein the similar document retrieval module is connected with the block chain cloud end in a bidirectional manner, the average matching module and the document extraction module are connected with each other in a bidirectional manner between the block chain cloud ends, the average matching module is respectively connected with the document extraction module and the similar document retrieval module input end in an electric manner, the document extraction module is electrically connected with the output module, the output module is wirelessly connected with an external display terminal, and the external display terminal can display the file output by the output module.
2. The system for retrieving financial information based on block chain as claimed in claim 1, wherein the data segment processing module comprises the following processing steps:
the method comprises the following steps that firstly, a data segmentation processing module extracts symbols, expressions and language aids in financial information, the number of occurrences of the symbols is recorded as F, and the number of occurrences of the expressions and the language aids is recorded as B and Y;
secondly, the data segmentation processing module marks the main split words subjected to partitioning and records the occurrence frequency of the split words as C;
step three, adopting a formula
Calculating to obtain a word segment mean value CDi, wherein A1, A2, A3 and A4 are all preset coefficient factors, and A1 is more than A2 is more than A3 is more than A4 is more than 0;
and step four, calculating the word segment mean value CDi of the searched documents by adopting the same formula, matching the mean value by the mean value matching module, and extracting similar documents.
3. The financial information retrieval system based on the block chain as claimed in claim 2, wherein the similar document retrieval module is capable of extracting similar documents of the term mean, the mean matching module is capable of matching the calculated CDi and sending the matching degree to the document extraction module, the document extraction module is capable of extracting the system documents in the cloud of the block chain, and after extraction is completed, the output module outputs the extracted documents to enable an operator to extract the document data corresponding to the retrieval.
4. The system of claim 3, wherein the overlap ratio of the mean matching module is calculated by comparing the original segment mean value CDi with the CDi of the document in the cloud of the block chain, and the closer the comparison value is to 1, the more similar the document is to the corresponding search document.
5. The system of claim 4, wherein the similar document retrieval module extracts documents with contrast values within the interval of 0.8-0.9 by receiving data information inside the mean matching module, and records the documents as similar documents.
6. The system of claim 2, wherein the data segmentation processing module divides the splitting word before processing, determines which region the splitting word belongs to, and searches and extracts documents with the same splitting word in the cloud of the block chain.
7. The system of claim 1, wherein the data matching module is configured to perform extraction matching on the internal data of the blockchain cloud and send the matching data to the split-term partitioning module.
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| CN106682174A (en) * | 2016-12-28 | 2017-05-17 | 南华大学 | Big data application based short text information searching system |
| US20180300542A1 (en) * | 2017-04-18 | 2018-10-18 | Nuance Communications, Inc. | Drawing emojis for insertion into electronic text-based messages |
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