CN117076694A - Method, device, equipment and storage medium for storing and searching information fragments - Google Patents

Method, device, equipment and storage medium for storing and searching information fragments Download PDF

Info

Publication number
CN117076694A
CN117076694A CN202311029922.0A CN202311029922A CN117076694A CN 117076694 A CN117076694 A CN 117076694A CN 202311029922 A CN202311029922 A CN 202311029922A CN 117076694 A CN117076694 A CN 117076694A
Authority
CN
China
Prior art keywords
information
fragments
fragment
marks
user
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202311029922.0A
Other languages
Chinese (zh)
Inventor
刘威
李政
夏勇峰
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing Beehive Century Technology Co ltd
Original Assignee
Beijing Beehive Century Technology Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beijing Beehive Century Technology Co ltd filed Critical Beijing Beehive Century Technology Co ltd
Priority to CN202311029922.0A priority Critical patent/CN117076694A/en
Publication of CN117076694A publication Critical patent/CN117076694A/en
Pending legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/40—Information retrieval; Database structures therefor; File system structures therefor of multimedia data, e.g. slideshows comprising image and additional audio data
    • G06F16/41—Indexing; Data structures therefor; Storage structures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/40—Information retrieval; Database structures therefor; File system structures therefor of multimedia data, e.g. slideshows comprising image and additional audio data
    • G06F16/43—Querying
    • G06F16/435—Filtering based on additional data, e.g. user or group profiles
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/40—Information retrieval; Database structures therefor; File system structures therefor of multimedia data, e.g. slideshows comprising image and additional audio data
    • G06F16/45—Clustering; Classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/40—Information retrieval; Database structures therefor; File system structures therefor of multimedia data, e.g. slideshows comprising image and additional audio data
    • G06F16/48—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/483—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Multimedia (AREA)
  • Data Mining & Analysis (AREA)
  • Databases & Information Systems (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Library & Information Science (AREA)
  • Software Systems (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

The application provides a method, a device, equipment and a storage medium for storing and searching information fragments, wherein the method comprises the steps of collecting information fragments in the life of a user, wherein the information fragments comprise at least one of image fragments, sound fragments and text fragments; indexing the information fragments and corresponding fragment marks, and storing the information fragments and the fragment marks in a database in a classified manner, wherein the fragment marks comprise keyword marks or label marks; the information segments are searched from the database based on the relevant information entered by the user regarding the segment markers. The method can achieve the effects of reasonably storing and quickly searching information in life.

Description

Method, device, equipment and storage medium for storing and searching information fragments
Technical Field
The present application relates to the field of intelligent ARs, and in particular, to a method, apparatus, device, and storage medium for storing and searching information fragments.
Background
Currently, in daily life, people encounter many pieces of information that need to be recorded and memorized, such as photos, text, and sound clips. Traditional memory methods often store the information in different places and search the information by means of classified storage.
However, since the amount of stored information is large, it is difficult to quickly acquire information required by a user despite the classified storage.
Therefore, how to reasonably store and quickly search information in life is a technical problem to be solved.
Disclosure of Invention
The embodiment of the application aims to provide a method for storing and searching information fragments, and the technical scheme of the embodiment of the application can achieve the effects of reasonably storing and quickly searching information in life.
In a first aspect, an embodiment of the present application provides a method for storing and searching information segments, which is applied to an augmented reality AR device, and includes collecting information segments in life of a user, where the information segments include at least one of an image segment, a sound segment, and a text segment; indexing the information fragments and corresponding fragment marks, and storing the information fragments and the fragment marks in a database in a classified manner, wherein the fragment marks comprise keyword marks or label marks; the information segments are searched from the database based on the relevant information entered by the user regarding the segment markers.
In the embodiment of the application, after various information in life is marked and indexed, the information is stored in the database through marked classification, and further, when the information is searched, the quick search can be realized according to marked related information input by a user, so that the effects of reasonably storing and quickly searching the information in life can be achieved.
In some embodiments, the collecting the pieces of information in the life of the user includes: periodically collecting a plurality of pieces of information in the life of the user through a component on the AR device; comparing the similarity between two adjacent information fragments in the collected information fragments to determine whether the two adjacent information fragments are identical; deleting a second information fragment in the two adjacent information fragments when the two adjacent information fragments are identical, so as to obtain the information fragments; and deleting the first information fragment in the two adjacent information fragments when the two adjacent information fragments are determined to be different, so as to obtain the information fragment.
In the embodiment of the application, the information fragments collected successively can be compared, whether the information fragments before and after are the same information fragment can be accurately compared in a similarity comparison mode, the information fragments collected later can be ignored when the information fragments are the same fragment, the information fragments collected earlier can be updated and deleted when the information fragments are not the same fragment, and the effects of effectively screening and storing the information can be achieved.
In some embodiments, the indexing the information segments and corresponding segment tags and storing the information segments and the segment tag classifications in a database comprises: acquiring the fragment mark input by a user or extracting the fragment mark from the information fragment; extracting information characteristics of the information fragments, and converting the information characteristics into binary codes through a hash function; classifying the segment marks, and storing the segment marks and the binary codes in the database in a multi-dimensional index mode.
In the embodiment of the application, the characteristics of the fragment information can be stored in the form of binary codes, the storage space can be saved, and meanwhile, the information can be searched quickly according to the binary codes when the information is searched.
In some embodiments, said searching said information piece from said database based on said user entered relevant information about said piece tags comprises: acquiring input data manually input by the user, and searching the information fragments from the database, wherein the input data comprises characters, images, sounds or labels; or acquiring the voice input by the user, and searching the information fragment from the database.
In the embodiment of the application, the identification and analysis can be rapidly performed according to the input of different forms of users, and further the information fragments stored in the database can be rapidly searched according to the analysis result.
In some embodiments, the obtaining input data manually entered by the user, searching the database for the piece of information, comprises: extracting key information in the input data; calculating a plurality of similarities of the key information and a plurality of fragment marks stored in a database; screening the fragment marks corresponding to the highest similarity in the plurality of similarities; and displaying the information fragment corresponding to the fragment mark through a display module of the AR equipment.
In the embodiment of the application, the corresponding fragment mark can be matched in a mode of extracting the key information, so that the effect of quickly searching the information fragment is achieved.
In some embodiments, the obtaining the voice input by the user, searching the information segment from the database, includes: recognizing the voice input by the user to obtain a target text; extracting keywords in the target text; and searching the information fragment through the keyword or executing a corresponding operation instruction through the keyword.
In the above embodiment of the present application, the effects of the related functions of different AR devices may also be achieved by recognizing the voice of the user.
In some embodiments, the related information is text, image or voice related to the segment tags.
In the above embodiment of the present application, the related information may be various information about the segment tags, so that it is convenient to match the segment tags according to different information.
In a second aspect, an embodiment of the present application provides an apparatus for storing and searching an information fragment, including:
the collecting module is used for collecting information fragments in the life of a user, wherein the information fragments comprise at least one of image fragments, sound fragments and text fragments;
the indexing module is used for indexing the information fragments and the corresponding fragment marks, and storing the information fragments and the fragment marks in a database in a classified manner, wherein the fragment marks comprise keyword marks or label marks;
and the searching module is used for searching the information fragments from the database according to the relevant information about the fragment marks input by the user.
Optionally, the collecting module is specifically configured to:
periodically collecting a plurality of pieces of information in the life of the user through a component on the AR device;
comparing the similarity between two adjacent information fragments in the collected information fragments to determine whether the two adjacent information fragments are identical;
deleting a second information fragment in the two adjacent information fragments when the two adjacent information fragments are identical, so as to obtain the information fragments;
and deleting the first information fragment in the two adjacent information fragments when the two adjacent information fragments are determined to be different, so as to obtain the information fragment.
Optionally, the indexing module is specifically configured to:
acquiring the fragment mark input by a user or extracting the fragment mark from the information fragment;
extracting information characteristics of the information fragments, and converting the information characteristics into binary codes through a hash function;
classifying the segment marks, and storing the segment marks and the binary codes in the database in a multi-dimensional index mode.
Optionally, the search module is specifically configured to:
acquiring input data manually input by the user, and searching the information fragments from the database, wherein the input data comprises characters, images, sounds or labels;
or alternatively
And acquiring the voice input by the user, and searching the information fragment from the database.
Optionally, the search module is specifically configured to:
extracting key information in the input data;
calculating a plurality of similarities of the key information and a plurality of fragment marks stored in a database;
screening the fragment marks corresponding to the highest similarity in the plurality of similarities;
and displaying the information fragment corresponding to the fragment mark through a display module of the AR equipment.
Optionally, the search module is specifically configured to:
recognizing the voice input by the user to obtain a target text;
extracting keywords in the target text;
and searching the information fragment through the keyword or executing a corresponding operation instruction through the keyword.
Optionally, the related information is text, image or voice related to the segment mark.
In a third aspect, an embodiment of the present application provides an electronic device comprising a processor and a memory storing computer readable instructions which, when executed by the processor, perform the steps of the method as provided in the first aspect above.
In a fourth aspect, embodiments of the present application provide a readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the method as provided in the first aspect above.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the embodiments of the application. The objectives and other advantages of the application will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope, and other related drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of a method for storing and searching information segments according to an embodiment of the present application;
FIG. 2 is a flowchart of an implementation method for storing and searching information segments according to an embodiment of the present application;
FIG. 3 is a schematic block diagram of an apparatus for storing and searching information segments according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an apparatus for storing and searching information fragments according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only to distinguish the description, and are not to be construed as indicating or implying relative importance.
The method is applied to intelligent AR storage and information searching scenes, and the specific scenes are indexing of the fragment information and the fragment marks, then storing the fragment information and the fragment marks in a database in a classified mode, matching the fragment marks according to information input by a user during searching, and obtaining corresponding fragment information.
Currently, in daily life, people encounter many pieces of information that need to be recorded and memorized, such as photos, text, and sound clips. Traditional memory methods often store the information in different places and search the information by means of classified storage. However, since the amount of stored information is large, it is difficult to quickly acquire information required by a user despite the classified storage.
The application collects the information fragments in the life of the user, wherein the information fragments comprise at least one of image fragments, sound fragments and text fragments; indexing the information fragments and corresponding fragment marks, and storing the information fragments and the fragment marks in a database in a classified manner, wherein the fragment marks comprise keyword marks or label marks; the information segments are searched from the database based on the relevant information entered by the user regarding the segment markers. After various information in life is marked and indexed, the information is stored in a database through marked classification, and then quick search can be realized according to marked related information input by a user when the information is searched, so that the effects of reasonably storing and quickly searching the information in life can be achieved.
In the embodiment of the present application, the execution body may be an information fragment storage and search device in the information fragment storage and search system, and in practical application, the information fragment storage and search device may be electronic devices such as a terminal device and a server, which are not limited herein.
The method of storing and searching for an information fragment according to an embodiment of the present application will be described in detail with reference to fig. 1.
Referring to fig. 1, fig. 1 is a flowchart of a method for storing and searching information segments, which is applied to an augmented reality AR device according to an embodiment of the present application, where the method for storing and searching information segments shown in fig. 1 includes:
step 110: and collecting the information fragments in the life of the user.
Wherein the information segment includes at least one of an image segment, a sound segment, and a text segment. The image clip may be some information such as pictures and conversations encountered in the life of the user shot by the AR device, the sound clip may be a voice clip of the conversation between the user and other people, and the text clip may be some text clip which the user inputs and is wanted to store, for example, daily work content, learning content or memo information.
In some embodiments of the present application, the collecting the pieces of information in the life of the user includes: periodically collecting a plurality of pieces of information in the life of the user through a component on the AR device; comparing the similarity between two adjacent information fragments in the collected information fragments to determine whether the two adjacent information fragments are identical; deleting a second information fragment in the two adjacent information fragments when the two adjacent information fragments are identical, so as to obtain the information fragments; and deleting the first information fragment in the two adjacent information fragments when the two adjacent information fragments are determined to be different, so as to obtain the information fragment.
In the process, the method can compare the information fragments collected successively, accurately compare whether the front and rear information fragments are the same information fragment in a similarity comparison mode, ignore the information fragments collected later when the front and rear information fragments are the same fragment, update the information fragments collected earlier and delete the information fragments when the front and rear information fragments are not the same fragment, and achieve the effects of effectively screening and storing information.
The timing may be set according to the requirement, for example, 1s, and the adjacent information segments may be two adjacent pictures taken, two adjacent recorded voices, two input texts, etc. Deleting a second information fragment in the two adjacent information fragments when the two adjacent information fragments are identical, so as to obtain the information fragments; when the two adjacent pieces of information are different, deleting the first information piece in the two adjacent pieces of information to obtain the information piece, for example, when the similarity of the collected images is too large, considering that the two images are identical, directly deleting the images shot after the two images are deleted, when the similarity of the collected images is smaller, considering that the two images are not identical, directly deleting the images shot before the two images are deleted and storing the images shot after the two images are stored, realizing the updating of the images, or not deleting the images shot before the two images are stored together.
For example, the acquisition is a picture of a picture acquired every second by a camera in the AR glasses, and each picture is compared with a picture acquired in the last second. And comparing and determining the picture to be acquired. Some image compression algorithms are used to reduce the size of the picture. The similarity threshold value refers to the similarity degree between two pictures, and if the similarity degree is lower than the threshold value, the pictures are considered to be different and need to be acquired; if above the threshold, then the same or similar frames are considered, and acquisition is not required.
Step 120: indexing the information segments and corresponding segment labels, and storing the information segments and segment label classifications in a database.
Wherein the fragment tags include keyword tags or tag tags.
In some embodiments of the application, the indexing the information segments and corresponding segment tags and storing the information segments and the segment tag classifications in a database comprises: acquiring the fragment mark input by a user or extracting the fragment mark from the information fragment; extracting information characteristics of the information fragments, and converting the information characteristics into binary codes through a hash function; classifying the segment marks, and storing the segment marks and the binary codes in the database in a multi-dimensional index mode.
In the process, the method can store the characteristics of the fragment information in the form of binary codes, save the storage space and simultaneously can quickly search according to the binary codes when searching the information.
The information providing feature represents a mark capable of embodying the feature of the information fragment, and is used for distinguishing different information fragments, such as key words or phrases in the information fragment. The multi-dimensional index mode can correlate the segment marks corresponding to the segment information with the binary codes, and therefore correlation storage is achieved.
For example, if the user adds a tag "travel" and a picture in the data is taken at the eiffel tower in paris, the indexing module may store the feature code and tag "travel" for the picture in the database so that the user can search for the picture by entering "travel" or uploading a similar picture.
Step 130: the information segments are searched from the database based on the relevant information entered by the user regarding the segment markers.
In some embodiments of the application, the related information is text, image or voice related to the segment labels.
In the process, the related information can be various information about the fragment mark, so that the fragment mark can be conveniently matched according to different information.
The related text, image or voice can be identified, corresponding key information, such as keywords, key images and the like, is extracted, and then the relevant information is extracted, so that the corresponding segment marks are matched.
In some embodiments of the present application, the searching the information piece from the database according to the related information about the piece tag input by the user includes: acquiring input data manually input by the user, and searching the information fragments from the database, wherein the input data comprises characters, images, sounds or labels; or acquiring the voice input by the user, and searching the information fragment from the database.
In the embodiment of the application, the identification and analysis can be rapidly performed according to the input of different forms of users, and further the information fragments stored in the database can be rapidly searched according to the analysis result.
The input data comprises characters, images, sounds or labels, and the characters, images, sounds or labels can be identified to match corresponding segment marks, so that corresponding information segments are obtained.
In some embodiments of the present application, the acquiring input data manually input by the user, searching the information piece from the database, includes: extracting key information in the input data; calculating a plurality of similarities of the key information and a plurality of fragment marks stored in a database; screening the fragment marks corresponding to the highest similarity in the plurality of similarities; and displaying the information fragment corresponding to the fragment mark through a display module of the AR equipment.
In the process, the method can match the corresponding fragment mark in a mode of extracting the key information, so that the effect of quickly searching the information fragment is achieved.
The key information may be keywords, phrases, images, etc.
In some embodiments of the present application, the obtaining the voice input by the user, searching the information piece from the database includes: recognizing the voice input by the user to obtain a target text; extracting keywords in the target text; and searching the information fragment through the keyword or executing a corresponding operation instruction through the keyword.
In the process, the application can also realize the effect of the related functions of different AR equipment by recognizing the voice of the user.
When searching the information fragments through the keywords, the corresponding fragment information can be acquired after the key information is matched with the marks of the fragments. The corresponding operation instruction is executed through the keyword, and the corresponding function instruction can be matched through the related function of the AR equipment input by the user, so that the corresponding function is executed according to the instruction.
For example, if a user enters a word "Paris," the search module may query the database for data containing the keyword or phrase "Paris" using an inverted index, calculate their matches to the user input, and display the highest matches to the user. The user may see thumbnail images and text descriptions of pictures and sounds in the data through AR glasses and may choose to view more details or perform other operations.
For example: the user may activate the voice interaction function of the AR glasses, e.g. "hi, glasses", by speaking "wake-up word". The user may search by speaking "search terms," such as "search for tourist attractions to Paris. The user can perform operations by speaking the "instruction word", such as "open the first piece of data" or "return to the previous layer". The user may evaluate or suggest a system by speaking the "feedback word," such as "this system works well" or "hopes to add a favorites function. The system may give feedback to the user by means of speech output, e.g. "data have been found for you, please select data you want to view" or "thank you for your feedback, we will strive to improve".
In the process shown in fig. 1, the application collects the information fragments in the life of the user, wherein the information fragments comprise at least one of image fragments, sound fragments and text fragments; indexing the information fragments and corresponding fragment marks, and storing the information fragments and the fragment marks in a database in a classified manner, wherein the fragment marks comprise keyword marks or label marks; the information segments are searched from the database based on the relevant information entered by the user regarding the segment markers. After various information in life is marked and indexed, the information is stored in a database through marked classification, and then quick search can be realized according to marked related information input by a user when the information is searched, so that the effects of reasonably storing and quickly searching the information in life can be achieved.
The following describes in detail the implementation method of information fragment storage and search according to the embodiment of the present application with reference to fig. 2.
Referring to fig. 2, fig. 2 is a flowchart of an implementation method of information fragment storage and search, which is applied to an augmented reality AR device, and the implementation method of information fragment storage and search shown in fig. 2 includes:
step 210: and collecting the information fragments in the life of the user.
Specific: periodically collecting a plurality of pieces of information in the life of the user through a component on the AR device; comparing the similarity between two adjacent information fragments in the collected information fragments to determine whether the two adjacent information fragments are identical; deleting a second information fragment in the two adjacent information fragments when the two adjacent information fragments are identical, so as to obtain the information fragments; and deleting the first information fragment in the two adjacent information fragments when the two adjacent information fragments are determined to be different, so as to obtain the information fragment.
Step 220: and extracting key information of the information fragment to obtain the label mark.
Specific: and extracting key information content of the information fragment, and matching the label mark corresponding to the key information.
Step 230: indexing the information segments and corresponding segment labels, and storing the information segments and segment label classifications in a database.
Specific: acquiring the fragment mark input by a user or extracting the fragment mark from the information fragment; extracting information characteristics of the information fragments, and converting the information characteristics into binary codes through a hash function; classifying the segment marks, and storing the segment marks and the binary codes in the database in a multi-dimensional index mode.
Step 240: the information segments are searched from the database based on the relevant information entered by the user regarding the segment markers.
Specific: acquiring input data manually input by the user, and searching the information fragments from the database, wherein the input data comprises characters, images, sounds or labels; or acquiring the voice input by the user, and searching the information fragment from the database.
In addition, the specific method and steps shown in fig. 2 may refer to the method shown in fig. 1, and will not be described in detail herein.
The method of information fragment storage and searching was described above by means of fig. 1-2, and the apparatus of information fragment storage and searching is described below in connection with fig. 3-4.
Referring to fig. 3, a schematic block diagram of an apparatus 300 for storing and searching information fragments according to an embodiment of the present application is shown, where the apparatus 300 may be a module, a program segment, or a code on an electronic device. The apparatus 300 corresponds to the embodiment of the method of fig. 1 described above, and is capable of performing the steps involved in the embodiment of the method of fig. 1. Specific functions of the apparatus 300 will be described below, and detailed descriptions thereof will be omitted herein as appropriate to avoid redundancy.
Optionally, the apparatus 300 includes:
a collecting module 310, configured to collect information pieces in life of a user, where the information pieces include at least one of an image piece, a sound piece, and a text piece;
an indexing module 320, configured to index the information fragment and the corresponding fragment tag, and store the information fragment and the fragment tag in a database in a classification manner, where the fragment tag includes a keyword tag or a tag;
and a searching module 330, configured to search the information fragment from the database according to the relevant information about the fragment mark input by the user.
Optionally, the collecting module is specifically configured to:
periodically collecting a plurality of pieces of information in the life of the user through a component on the AR device; comparing the similarity between two adjacent information fragments in the collected information fragments to determine whether the two adjacent information fragments are identical; deleting a second information fragment in the two adjacent information fragments when the two adjacent information fragments are identical, so as to obtain the information fragments; and deleting the first information fragment in the two adjacent information fragments when the two adjacent information fragments are determined to be different, so as to obtain the information fragment.
Optionally, the indexing module is specifically configured to:
acquiring the fragment mark input by a user or extracting the fragment mark from the information fragment; extracting information characteristics of the information fragments, and converting the information characteristics into binary codes through a hash function; classifying the segment marks, and storing the segment marks and the binary codes in the database in a multi-dimensional index mode.
Optionally, the search module is specifically configured to:
acquiring input data manually input by the user, and searching the information fragments from the database, wherein the input data comprises characters, images, sounds or labels; or acquiring the voice input by the user, and searching the information fragment from the database.
Optionally, the search module is specifically configured to:
extracting key information in the input data; calculating a plurality of similarities of the key information and a plurality of fragment marks stored in a database; screening the fragment marks corresponding to the highest similarity in the plurality of similarities; and displaying the information fragment corresponding to the fragment mark through a display module of the AR equipment.
Optionally, the search module is specifically configured to:
recognizing the voice input by the user to obtain a target text; extracting keywords in the target text; and searching the information fragment through the keyword or executing a corresponding operation instruction through the keyword.
Optionally, the related information is text, image or voice related to the segment mark.
Referring to fig. 4, a schematic block diagram of an apparatus for storing and searching information fragments according to an embodiment of the present application may include a memory 410 and a processor 420. Optionally, the apparatus may further include: a communication interface 430 and a communication bus 440. The apparatus corresponds to the embodiment of the method of fig. 1 described above, and is capable of performing the steps involved in the embodiment of the method of fig. 1, and specific functions of the apparatus may be found in the following description.
In particular, the memory 410 is used to store computer readable instructions.
The processor 420, which processes the readable instructions stored in the memory, is capable of performing the various steps in the method of fig. 1.
Communication interface 430 is used for signaling or data communication with other node devices. For example: for communication with a server or terminal, or with other device nodes, although embodiments of the application are not limited in this regard.
A communication bus 440 for enabling direct connection communication of the above-described components.
The communication interface 430 of the device in the embodiment of the present application is used for performing signaling or data communication with other node devices. The memory 410 may be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one disk memory. Memory 410 may also optionally be at least one storage device located remotely from the aforementioned processor. The memory 410 has stored therein computer readable instructions which, when executed by the processor 420, perform the method process described above in fig. 1. Processor 420 may be used on apparatus 300 and to perform functions in the present application. By way of example, the processor 420 described above may be a general purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), an off-the-shelf programmable gate array (Field Programmable Gate Array, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, and the embodiments of the application are not limited in this regard.
Embodiments of the present application also provide a readable storage medium, which when executed by a processor, performs a method process performed by an electronic device in the method embodiment shown in fig. 1.
It will be clear to those skilled in the art that, for convenience and brevity of description, reference may be made to the corresponding procedure in the foregoing method for the specific working procedure of the apparatus described above, and this will not be repeated here.
In summary, the embodiments of the present application provide a method, an apparatus, a device, and a storage medium for storing and searching information segments, where the method includes collecting information segments in life of a user, where the information segments include at least one of image segments, sound segments, and text segments; indexing the information fragments and corresponding fragment marks, and storing the information fragments and the fragment marks in a database in a classified manner, wherein the fragment marks comprise keyword marks or label marks; the information segments are searched from the database based on the relevant information entered by the user regarding the segment markers. The method can achieve the effects of reasonably storing and quickly searching information in life.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The apparatus embodiments described above are merely illustrative, for example, of the flowcharts and block diagrams in the figures that illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form a single part, or each module may exist alone, or two or more modules may be integrated to form a single part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and variations will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application. It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

Claims (10)

1. A method of information clip storage and search, characterized by being applied to an augmented reality AR device, comprising:
collecting information fragments in the life of a user, wherein the information fragments comprise at least one of image fragments, sound fragments and text fragments;
indexing the information fragments and corresponding fragment marks, and storing the information fragments and the fragment marks in a database in a classified manner, wherein the fragment marks comprise keyword marks or label marks;
and searching the information fragment from the database according to the relevant information about the fragment mark input by the user.
2. The method of claim 1, wherein the collecting the pieces of information in the life of the user comprises:
periodically collecting a plurality of pieces of information in the life of the user through a component on the AR device;
comparing the similarity between two adjacent information fragments in the collected information fragments to determine whether the two adjacent information fragments are identical;
deleting a second information fragment in the two adjacent information fragments when the two adjacent information fragments are identical, so as to obtain the information fragments;
and deleting the first information fragment in the two adjacent information fragments when the two adjacent information fragments are determined to be different, so as to obtain the information fragment.
3. The method of claim 1 or 2, wherein indexing the information pieces and corresponding piece tags and storing the information pieces and the piece tag classifications in a database comprises:
acquiring the fragment mark input by a user or extracting the fragment mark from the information fragment;
extracting information characteristics of the information fragments, and converting the information characteristics into binary codes through a hash function;
classifying the segment marks, and storing the segment marks and the binary codes in the database in a multi-dimensional index mode.
4. A method according to claim 1 or 2, wherein said searching said information pieces from said database based on said user entered relevant information about said piece tags, comprises:
acquiring input data manually input by the user, and searching the information fragments from the database, wherein the input data comprises characters, images, sounds or labels;
or alternatively
And acquiring the voice input by the user, and searching the information fragment from the database.
5. The method of claim 4, wherein the obtaining input data manually entered by the user, searching the database for the pieces of information, comprises:
extracting key information in the input data;
calculating a plurality of similarities of the key information and a plurality of fragment marks stored in a database;
screening the fragment marks corresponding to the highest similarity in the plurality of similarities;
and displaying the information fragment corresponding to the fragment mark through a display module of the AR equipment.
6. The method of claim 4, wherein the retrieving the user-entered speech, searching the database for the pieces of information, comprises:
recognizing the voice input by the user to obtain a target text;
extracting keywords in the target text;
and searching the information fragment through the keyword or executing a corresponding operation instruction through the keyword.
7. A method according to claim 1 or 2, wherein the relevant information is text, images or speech associated with the segment tags.
8. An apparatus for storing and searching information pieces, comprising:
the collecting module is used for collecting information fragments in the life of a user, wherein the information fragments comprise at least one of image fragments, sound fragments and text fragments;
the indexing module is used for indexing the information fragments and the corresponding fragment marks, and storing the information fragments and the fragment marks in a database in a classified manner, wherein the fragment marks comprise keyword marks or label marks;
and the searching module is used for searching the information fragments from the database according to the relevant information about the fragment marks input by the user.
9. An electronic device, comprising:
a memory and a processor, the memory storing computer readable instructions that, when executed by the processor, perform the steps in the method of any of claims 1-7.
10. A computer-readable storage medium, comprising:
computer program which, when run on a computer, causes the computer to perform the method according to any of claims 1-7.
CN202311029922.0A 2023-08-16 2023-08-16 Method, device, equipment and storage medium for storing and searching information fragments Pending CN117076694A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202311029922.0A CN117076694A (en) 2023-08-16 2023-08-16 Method, device, equipment and storage medium for storing and searching information fragments

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202311029922.0A CN117076694A (en) 2023-08-16 2023-08-16 Method, device, equipment and storage medium for storing and searching information fragments

Publications (1)

Publication Number Publication Date
CN117076694A true CN117076694A (en) 2023-11-17

Family

ID=88701652

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202311029922.0A Pending CN117076694A (en) 2023-08-16 2023-08-16 Method, device, equipment and storage medium for storing and searching information fragments

Country Status (1)

Country Link
CN (1) CN117076694A (en)

Similar Documents

Publication Publication Date Title
CN109815364B (en) Method and system for extracting, storing and retrieving mass video features
TWI553494B (en) Multi-modal fusion based Intelligent fault-tolerant video content recognition system and recognition method
CN111694965B (en) Image scene retrieval system and method based on multi-mode knowledge graph
CN111291210B (en) Image material library generation method, image material recommendation method and related devices
CN111191022B (en) Commodity short header generation method and device
US20100114856A1 (en) Information search apparatus, information search method, and storage medium
EP2291765A2 (en) Statistical approach to large-scale image annotation
CN106557545A (en) Video retrieval method and device
CN111368048A (en) Information acquisition method and device, electronic equipment and computer readable storage medium
KR102373884B1 (en) Image data processing method for searching images by text
JPWO2008032780A1 (en) Retrieval method, similarity calculation method, similarity calculation and same document collation system, and program thereof
CN111353055B (en) Cataloging method and system based on intelligent tag extension metadata
KR101472451B1 (en) System and Method for Managing Digital Contents
CN114443847A (en) Text classification method, text processing method, text classification device, text processing device, computer equipment and storage medium
CN113992944A (en) Video cataloging method, device, equipment, system and medium
CN113254665A (en) Knowledge graph expansion method and device, electronic equipment and storage medium
CN106372123B (en) Tag-based related content recommendation method and system
CN111178349A (en) Image identification method, device, equipment and storage medium
CN103093213A (en) Video file classification method and terminal
CN117076694A (en) Method, device, equipment and storage medium for storing and searching information fragments
CN115203445A (en) Multimedia resource searching method, device, equipment and medium
CN114817586A (en) Target object classification method and device, electronic equipment and storage medium
CN114218437A (en) Adaptive picture clipping and fusing method, system, computer device and medium
CN112241463A (en) Search method based on fusion of text semantics and picture information
JP4844737B2 (en) Representative information selection method, representative information selection system, and program

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination