WO2020140360A1 - 基于剪贴板进行信息推送的方法、系统及终端设备 - Google Patents

基于剪贴板进行信息推送的方法、系统及终端设备 Download PDF

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Publication number
WO2020140360A1
WO2020140360A1 PCT/CN2019/086270 CN2019086270W WO2020140360A1 WO 2020140360 A1 WO2020140360 A1 WO 2020140360A1 CN 2019086270 W CN2019086270 W CN 2019086270W WO 2020140360 A1 WO2020140360 A1 WO 2020140360A1
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Prior art keywords
word segmentation
user
segmentation data
information
text information
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PCT/CN2019/086270
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English (en)
French (fr)
Inventor
吴琨
丁翔
冯天骁
王瑞鑫
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上海触乐信息科技有限公司
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Publication of WO2020140360A1 publication Critical patent/WO2020140360A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G06F16/335—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
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9535—Search customisation based on user profiles and personalisation

Definitions

  • Embodiments of the present invention relate to information processing technology, and in particular, to a method, system, and terminal device for pushing information based on a clipboard.
  • users In daily life, users often have the need to obtain further information when chatting or browsing the web. For example, when users encounter interesting content or hot topics during chat, users want to learn more information to participate in the chat; and Or, the user sees a product used by another user while browsing Weibo, and the user wants to purchase the product.
  • the current common practice is that the user manually opens the corresponding application according to the information that he wants to obtain, enters keywords in the search box of the application to search, and then filters among several search results Out what you want.
  • the prior art also provides a search solution based on the content copied by the user. Taking WeChat as an example, the user can perform a long press operation on the public account tweet page to select the copy function, and then select the keywords to be retrieved. Select the "Search" option in the given function options, and then jump to the application selection page to select the corresponding application to search for keywords.
  • the user when the user wants to retrieve more information, the user needs to manually enter the next keyword in the application after searching the last keyword to continue the search. According to different retrieval needs, the user also needs to switch to Retrieve keywords in different applications; or, after searching the last keyword, the user returns to the WeChat page and selects the next keyword according to the method in the second scheme above to continue searching until all the keywords are retrieved Keywords. It can be seen that once the user wants to retrieve more information, the prior art solution will consume a lot of the user's time and seriously reduce the user's efficiency in obtaining information.
  • Embodiments of the present invention provide a method, system, and terminal device for pushing information based on a clipboard to save user information acquisition time, reduce user operations, and improve user information acquisition efficiency.
  • a method, system and terminal device for pushing information based on a clipboard includes: acquiring text information copied/cut into the clipboard; and segmenting the text information , Obtain at least one word segmentation data, and display the word segmentation data, the word segmentation data is a subset of text information; detect the word segmentation data selected by the user; based on the context information associated with the text information, user history chat records, or user portraits At least one of: searching the selected word segmentation data and filtering the search results to obtain recommendation information associated with the selected word segmentation data; displaying the recommendation information.
  • a clipboard-based information pushing system wherein the system includes: a processing device, a storage device, an input device, and a display device; the input device is adapted to detect user-executed An input operation; wherein the input operation includes at least a copy/cut operation and selection of word segmentation data; the processing device is adapted to perform a segmentation operation and a push operation; wherein the segmentation operation includes at least: according to A copy/cut operation obtained by the input device to obtain copied/cut text information; divide the text information to obtain at least one word segmentation data; send the word segmentation data to a display device; wherein, the word segmentation The data is a subset of the text information; and the push operation includes at least: obtaining the selected word segmentation data according to the user operation obtained by the input device; according to the context information associated with the text information and the user's historical chat record Or at least one of the user portraits, retrieve the selected word segmentation data, and filter the search results to obtain recommendation information associated
  • a terminal device including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the program executed by the processor includes the program disclosed in this application Either way.
  • the clipboard-based information push mechanism can be configured to obtain text information that the user has copied or cut, by dividing the text information into at least one word segmentation data, and according to the user's selection Word segmentation data and context information associated with the text information or related user information, and then search and filter to obtain the associated recommendation information and prompt the user, so that the user can quickly obtain the association with the word segmentation data through the information push system
  • the recommended information saves information acquisition time, reduces repeated operations, and improves information acquisition efficiency.
  • FIG. 1 is a schematic diagram of a clipboard-based information push system provided by an embodiment of the present invention
  • FIG. 2 is a schematic flowchart of a clipboard-based information pushing method provided by an embodiment of the present invention
  • FIG. 3 is a schematic flowchart of an embodiment provided in step S2 shown in FIG. 2;
  • FIGS. 4a-d are schematic diagrams of a clipboard-based information storage and push interface provided by an embodiment of the present invention.
  • FIG. 5a-b are schematic flowcharts provided by an embodiment of step S28 shown in FIG. 3;
  • FIG. 6 is a schematic flowchart of an embodiment provided in step S3 shown in FIG. 2;
  • step S4 shown in FIG. 2;
  • FIG. 8a-b are schematic diagrams of an interface provided by an embodiment of step S5 shown in FIG. 2;
  • FIG. 9 is a schematic flowchart of a clipboard-based information pushing method provided by another embodiment of the present invention.
  • FIG. 10 is a schematic flowchart of a clipboard-based information pushing method according to another embodiment of the present invention.
  • each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, which contains one or more Executable instructions.
  • each block in the block diagrams and/or flowcharts and combinations of blocks in the block diagrams and/or flowcharts can be implemented with dedicated hardware-based systems that perform specified functions or operations, or can It is implemented with a combination of dedicated hardware and computer instructions.
  • FIG. 1 shows a block diagram of an exemplary clipboard-based information push system.
  • the information push system may be a mobile terminal including a display screen, such as a mobile phone, smart phone, PDA, or tablet computer, or other electronic devices that can interact with the Internet, such as cameras, wearable electronic devices, Car navigation equipment, electronic interactive terminals installed in public places such as stations or schools.
  • the information push system can access the network through broadband, such as ADSL, VDSL, optical fiber, wireless, cable TV, satellite, etc., or through narrowband, such as telephone dial-up access, GPRS, 2G, 3G, etc., or It can also access telecommunication networks through CDMA, 2G, 3G, 4G and other technologies.
  • broadband such as ADSL, VDSL, optical fiber, wireless, cable TV, satellite, etc.
  • narrowband such as telephone dial-up access, GPRS, 2G, 3G, etc.
  • CDMA Code Division Multiple Access
  • 2G, 3G, 4G Code Division Multiple Access
  • the information pushing system may be configured to record the text information copied/cut by the user, and divide the text information into at least one word segmentation data, detect the user's selection, determine the word segmentation data selected by the user, and then According to the context information associated with the text information, or the information associated with the user, such as the user portrait or the user's historical chat record, the selected analysis data is searched and filtered to obtain the associated recommendation information, so that the user can pass the information
  • the push system quickly obtains information associated with word segmentation data.
  • the clipboard may be an area in the system memory suitable for storing information copied or cut by the user.
  • the information push system can also configure the clipboard to store the user's historical copy or cut information in the clipboard for a long time, so that the user can view it at any time, or edit the records in the clipboard to save the required text information .
  • the information pushing system may also detect text information copied or cut to the clipboard by the user, mark the times of the same text information, and display the times marked information in the clipboard with the The corresponding position of the text information.
  • the information pushing system may also determine the display priority of the corresponding text information in the clipboard according to the times mark information, and sort the text information in the clipboard according to the display priority.
  • the clipboard may also be configured to store only the information temporarily copied or cut by the user as needed, and when new data is introduced, the original information is overwritten.
  • the information push system marks the number of times text messages copied or cut by users, and determines that “mailbox address 1” has the highest number of copies/cuts.
  • the number of times of copying/cutting of email address 2” is next, and the number of times of copying/cutting of other text information is less, it can be determined that the display priority of mailbox address 1 is higher than that of mailbox address 2, and the display priority of mailbox address 2 is higher than Other text information, and then sort the text information in the clipboard according to the display priority.
  • the information push system stores the content copied/cut by the user in any application program into the clipboard by setting the clipboard as a storage device according to the user's copy/cut operation; and, The clipboard obtains the text information accordingly and then automatically performs segmentation and personalized information recommendation, so that the information push system can obtain text information collected by users in different applications across applications, and on this basis, achieve The acquisition of word segmentation data and the retrieval of recommended information improve the versatility of the information push system. It is worth mentioning that this information push system is particularly important in mobile terminal devices.
  • some embodiments of the present application can realize the active storage and intelligent segmentation of the cut or copied text information, and can enable the stored text information, the segmented word segmentation data and its corresponding recommendation information to be in Called between applications that are the same as or different from the user's copy/cut operation, so that users can easily obtain associated recommended information through copy/cut operations between multiple applications, saving information acquisition time and reducing It has been repeated many times, which improves the efficiency of information acquisition.
  • the term "text information" may be a character that does not contain a picture, including text, letters, numbers, or any type of symbol corresponding to any language, where the symbol may be, for example, a punctuation mark, an arithmetic symbol, an emoticon,
  • the text information can be plain text, pure letters, pure numbers, pure symbols, or any combination of the above types of information, such as web addresses, email addresses, etc.
  • the "text information" may be information copied/cut by the user in any application scenario, for example, chat information copied/cut by the user in a chat scenario, or for example, current news copied by the user in a news application
  • the URL Uniform Resource Locator
  • word segmentation data refers to a subset of text information that has been segmented according to certain segmentation rules.
  • the length of the segmentation data is less than the length of the text information.
  • the term "user portrait” is used to describe a series of tags of users, by actively or passively collecting various data left by users on the Internet, and further analyzing and processing these data to form a description The user's label.
  • “User profile” is used broadly to include at least one of the following: the user's personal information, such as the user's age, gender, height, weight, nationality, hometown, place of residence, education, occupation, skills, specialties, hobbies, etc.; Information related to user equipment, such as real-time location information of user equipment, model of user equipment, system language used by user equipment, or other configuration information of user equipment; user history copy/cut habits, for example, users often copy text+ URL address, text + phone number, or text + email address, etc.; user history input habit, for example, users are only used to enter the domain name when entering a web address, and for example, users are used to not add a subject when chatting; "user portrait” can also include user habits
  • the applications used for example, the shopping applications that users are
  • the term "recommended information” may include at least one of the following, text information, picture information, URL address, audio, video, installation package, and so on.
  • the information pushing system may include a processing device 110, a storage device 120, an input device 130, and a display device 140.
  • the processor may be a central processing unit (“CPU") or a graphics processing unit (“GPU”).
  • the processing device 110 may include one or more printed circuit boards or micro-processing module chips to execute a sequence of computer program instructions To perform various methods that will be explained in more detail below.
  • the processing device 110 may be configured to obtain the text information copied/cut to the clipboard through the input device 130, and divide the text information, according to the user's operation on the word segmentation data, the user selects The word segmentation data is pasted into the current input area, or based on one or any combination of the context information associated with the text information, the user’s historical chat history, or the user’s portrait, search in the storage device 120 to obtain recommended information associated with the word segmentation data Then, the word segmentation data pasted into the current input area or the recommended information retrieved is presented through the display device 120.
  • the storage device 120 may include one or more of random access memory (“RAM”) and read-only memory (“ROM"). Computer program instructions may be accessed and read from ROM or any other suitable memory location, and loaded into RAM for processing device 110 to execute.
  • the storage device 120 may store one or more software applications.
  • the software applications stored in the storage device 120 may include operating systems for general computer systems and devices for software control.
  • the storage device 120 may store the entire software application or only a part of the software application that may be executed by the processing device 110.
  • the storage device 120 may store information pushing software executable by the processing device 110 and perform an information pushing method.
  • the storage device 120 may include a clipboard and a database containing recommended information.
  • the database may be a local database or a cloud database, or may be partially local and partially cloud.
  • the storage device 120 also stores the user's historical chat information and data associated with the user's portrait, for example, the user's history input record, user history copy/cut record, user use application record, or user Records of other operations, etc.
  • the input device 130 and the display device 140 may be coupled to the processing device 110 through appropriate interface circuits.
  • the input device 130 may be a mouse, a keyboard, a touch pad, or a touch screen, and is suitable for detecting input operations performed by the user, for example, the user selects a certain piece of text information through the mouse, and uses the keyboard shortcut keys to copy or cut For example, the user can perform operations such as clicking, double-clicking, long-pressing, sliding up, sliding down, sliding left, or right through the touch pad or touch screen.
  • the input device 130 may also include an inductive input device 130.
  • the input device 130 may be a voice input device 130 and a voice analysis device, where the user performs voice input through the voice input device 130, and the voice analysis device detects When there is a user's voice input, the voice content input by the user is recognized and the instruction is analyzed.
  • the recognition result may be operation information corresponding to the input voice, such as a copy operation, a cut operation, a selection operation, and the like.
  • the input device 130 may also include certain function keys through which the user can initiate certain processes performed by the information push system, or otherwise interact with the information push system.
  • the display device 140 may include one or more display screens that display text or graphics to the user.
  • the display device 140 may display a GUI.
  • the information pushing system further includes a network interface 150, and the network interface 150 can provide a communication connection, so that the information pushing system can be connected to the cloud 160 through the network interface 150.
  • FIG. 2 shows a flowchart of an information pushing method provided by an embodiment of the present invention, including:
  • the corresponding text information can be obtained by detecting the user's operation.
  • the processing device 110 correspondingly acquires the user's copy/cut information, for example, the user receives another user while chatting with another user in a chat application
  • the user wants to know more about bitcoin, and performs a copy operation on the “bitcoin latest news www.****.com”.
  • the processing device 110 obtains the “bitcoin latest news www.
  • the information push system can perform the copy/cut operation on the corresponding information in any application.
  • the information push system correspondingly obtains the text information copied/cut to the clipboard.
  • the corresponding recommendation information is obtained after operations such as segmentation and user selection of word segmentation data, that is to say, the information push system can recommend the corresponding recommendation information for the user in any application, so as to implement cross-application information recommendation and facilitate the user to quickly get recommendations Information to help users quickly read or chat.
  • the processing device 110 can also directly obtain the historical pasting information stored in the clipboard at any time when the information pushing system is running. For example, when the information pushing system is started, the processing device 110 obtains the information in the clipboard according to the corresponding obtaining rule.
  • the processing device 110 can obtain the text information copied/cut to the clipboard for the last time. For example, when the user has copied "Hawking" and “Time History” while browsing the Weibo, the processing device 110 Obtain the "time history" of the last time the user copied the information.
  • the processing device 110 may also obtain all text information copied/cut to the clipboard within the latest preset number of times, for example, the user copied the topic "when the property is in progress” while browsing Weibo, and then read The current affairs news has copied the "Real Estate Control Policy” and "Mortgage Interest Rate Ranking” successively. Assuming that the preset number is 2 times, the processing device 110 obtains the information of the "Residential Control Policy” and "Mortgage Interest Rate Ranking" that have been copied twice recently.
  • the processing device 110 may also obtain all text information copied/cut to the clipboard within a preset time, for example, the processing device 110 only obtains all text copied/cut to the clipboard within 24 hours information. Further, the text information acquired by the processing device 110 can also be updated in real time with the update of time and the update of the user's copy/cut content.
  • the processing device 110 can also obtain text information actively selected by the user in the clipboard. Specifically, the user can open the clipboard through the input device 130, and the clipboard correspondingly presents the user's historical copy/cut information, When the user selects certain historical information in the clipboard, the processing device 110 acquires the information selected by the user accordingly.
  • S2 Divide the text information to obtain at least one word segmentation data, and display the word segmentation data, where the word segmentation data is a subset of the text information.
  • FIG. 3 shows a flowchart of a specific method of step S2.
  • segmenting text information includes: S21, segmenting the text information according to a corresponding word segmentation algorithm.
  • the word segmentation algorithm can include a word segmentation method based on string matching, that is, to match the text information to be analyzed with the entry in the machine dictionary according to a certain strategy, if a certain string can be found in the dictionary, the match is successful, That is, a word segmentation data is identified.
  • the word segmentation algorithm also includes a word segmentation method based on understanding. Syntax and semantic analysis are performed simultaneously during segmentation. For different languages, different syntactic and semantic analysis rules can be used to segment the text information.
  • the text information when the acquired text information is "basketball star Yao Ming", the text information can be syntactically and semantically analyzed to determine that the text information is composed of three nouns "basketball", “star” and “Yao Ming", so The text information can be divided into three participle data "basketball”, "star” and "Yao Ming” according to part of speech.
  • the acquired text information when the acquired text information is "Basketball, Star, Yao, Ming", the text information can be directly divided into “Basketball”, "star,” and “Yao Ming” according to the space and part of speech.
  • the word segmentation algorithm can also include a word segmentation method based on statistics, which can determine the credibility of the word formation by determining the frequency of adjacent words, and then segment the text information, still taking the text information "basketball star Yao Ming" as an example, When the frequency of "Basketball” and “Star” co-occurring exceeds the preset frequency, at this time, "Basketball” and “Star” can be merged as a participle data, thus obtaining the participle data "Basketball Star” and "Yao Ming".
  • the word segmentation algorithm can also segment text information through a machine learning model.
  • the text information can also be segmented according to the type of word segmentation data, where the type of word segmentation data can include URL addresses, email addresses, phone numbers, and so on.
  • segmenting the text information may further include: S22, obtaining user segmentation habits according to user history pasting records or historical input records; and then, by S23, segmenting the text information according to user segmentation habits.
  • the processing device 110 can obtain the user's pasting records or historical input records by reading the log information, and obtain the user's segmentation habits after statistical analysis. For example, when working, developers often need to publish version link information in the group, or copy the version link published by others. Therefore, when entering or pasting, they often use the format information of "name + link” or "link + name” to deal with When the device 110 detects that the text information contains a name and a link, it may use "name + link” or "link + name” as a participle data to segment the text information, so that the user can later paste or forward the participle data To other users.
  • the processing device 110 can analyze the user's input habits by inputting records of the user's history. For example, users often use “like you” to express “I like you” when chatting. It can be seen that users are used to not adding their own subject when chatting. For example, Users often input “baidu.com” and “sina” when entering a web address. It can be seen that users are used to entering only domain names or some domain names when entering web addresses.
  • the word segmentation data "google.com” can be supplemented and edited to form New participle data "www.google.com”.
  • the supplemented and edited word segmentation data can directly replace the original word segmentation data, or the original word segmentation data and the new word segmentation data can be retained at the same time, so that the user can select according to the current needs.
  • the identity information of the sender of the text information can also be detected and added to the word segmentation data.
  • the identity information may be the sender's name or nickname. For example, when the user selects the word segmentation data "131****1111", the nickname of the sender who sent the word segmentation data is "User A”, and "User A” is added to the original word segmentation data "131 In "****1111", supplementary edited word segmentation data "user A+131****1111” is obtained.
  • the word segmentation data selected by the user may also be detected, when the type of the word segmentation data is a preset type, such as phone, email, etc., or the word segmentation data conforms to the user's input habits, such as the user's habit of entering "name +link” or "link+name” format information, then the identity information of the sender of the text information is detected, and the identity information is added to the word segmentation data.
  • the location for adding the identity information can be set according to a preset format, or can be set or adjusted according to the user's input habits.
  • adjusting the display order of the word segmentation data may specifically include: S25.
  • S25 When the obtained word segmentation data is more than two, perform matching analysis on the obtained word segmentation data according to the user portrait, and adjust the display order so as to match the user portrait Word segmentation data with a high degree of matching has a higher display priority.
  • the user profile records a series of label information used to describe the user, and is widely used to include at least one of the following: the user's personal information, such as the user's age, gender, height, weight, nationality, hometown, place of residence , Education, occupation, skills, specialties, interests, user habits, user preferences, etc.; information related to user equipment, such as real-time location information of user equipment, model of user equipment, system language used by user equipment, or other user equipment Configuration information, etc.
  • the user's personal information such as the user's age, gender, height, weight, nationality, hometown, place of residence , Education, occupation, skills, specialties, interests, user habits, user preferences, etc.
  • information related to user equipment such as real-time location information of user equipment, model of user equipment, system language used by user equipment, or other user equipment Configuration information, etc.
  • the processing device 110 may match the word segmentation data with each tag information recorded in the user portrait to determine the degree of matching between the word segmentation data and the user portrait. Specifically, the higher the correlation between the word segmentation data and the tag information in the user portrait, or the word segmentation The more tag information the data matches, the higher the degree of matching between the segmentation data and the user's portrait.
  • the processing device 110 determines the display priority of the word segmentation data according to the matching degree of the word segmentation data with the user portrait, so that the word segmentation data having a high matching degree with the user portrait has a higher display priority, and according to the display priority of the word segmentation data Adjust the display order of word segmentation data so that the word segmentation data with the highest relevance to the user is given priority to the user, which is convenient for the user to quickly select.
  • the user copied the title "'*' to change the network commentary while browsing the news, Liu Guoliang turned around this year", and obtained the segmentation data "*", “change” and “network commentary” after segmentation , "Liu Guoliang", “Turn around”, "This year”, according to the user portrait, users often browse the news about Liu Guoliang, match the user portrait with these word segmentation data, and determine the participle data "Liu Guoliang” and the user portrait The highest degree of matching, followed by the word segmentation data "*”, then the word segmentation data "network commentary”, then adjust the display order of the word segmentation data to "Liu Guoliang", “*", “network commentary”, “change”, “turn around” ,”This year”.
  • the processing device may also reduce the display priority of non-meaningful word segmentation data, such as " ⁇ ”, “ ⁇ ”, “YES”, display the word segmentation data later, or directly filter out these non-actual Word segmentation data for meaning.
  • the user copied the chat message ""Dear Basketball” produced by Kobe Investment” during the group chat, and obtained the segmentation data ""Dear Basketball”” and “Yes” after segmentation.
  • “Kobe”, “investment production”, “de” according to the user portrait, the user's hobbies include playing basketball, and the user often browses information about the NBA, and matches the user portrait with these participle data to determine
  • the word segmentation data "Kobe” matches the user's portrait the most, and then the word segmentation data "Dear Basketball", and furthermore, the meaningless word segmentation data "Yes” and “De” can be filtered out, as shown in 4c Word segmentation data.
  • adjusting the display order of the word segmentation data may further include: S26.
  • S26 When the obtained word segmentation data is more than two, perform heat analysis on the word segmentation data according to the current hot word or hot topic, and adjust the display order so that The word segmentation data associated with the current hot word or hot topic has a higher display priority.
  • the hot words or hot topics can be counted based on the frequency of keywords entered by a large number of users, and the popularity of the hot words or hot topics can be determined according to the number of times the keywords are entered; the hot words/hot topics can also be obtained directly from third-party websites And the corresponding popularity, then the word segmentation data is matched with the current hot word/hot topic to determine the popularity of the word segmentation data, and then the display order of the word segmentation data is adjusted according to the heat of the word segmentation data.
  • the user copied the chat message "Do you know Bitcoin?" sent by other users.
  • the segmentation data "You”, “Know”, “Bitcoin”, “Do you?" Bitcoin is the current hot word, you can adjust the display order of the word segmentation data "Bitcoin” to the front.
  • the display priority of the word segmentation data may also be determined according to a default setting rule or a user setting rule, and then the display order of the word segmentation data may be adjusted according to the display priority. For example, it is stipulated that the telephone display priority>mail address display priority>URL address display priority.
  • S27 is executed to display the word segmentation data.
  • the word segmentation data may be displayed in the form of a card.
  • the word segmentation data may be presented in the card in a list according to the display priority.
  • the word segmentation data can also be displayed in the form of bubbles.
  • each bubble can carry one word segmentation data, and the display order of the bubble can be determined according to the display priority of the word segmentation data.
  • the bubbles can be displayed in a horizontal arrangement or in a vertical arrangement (only the horizontal arrangement is shown in FIG. 4d). Further, when there is a lot of word segmentation data, and the current display interface cannot present all the word segmentation data at the same time, you can also drag the word segmentation data left/right/up and down to display the sorted word segmentation data later, or you can enter into Figure 4a Show the detail page to display more word segmentation data.
  • step S2 after obtaining at least one word segmentation data, it is also possible to detect whether the user switches to another application through S28, and adjust the display of the word segmentation data according to the application switched by the user.
  • S28 specifically includes:
  • the type of application may include at least one of the following: browser, mailbox, phone book, toll free, shopping, online store, etc.
  • the input box may be the input box where the current cursor is located, and the attribute information of the input box may include a text type input box, a number type input box, a web address input box, a mixed type input box, and so on.
  • the processing device 110 when the user switches to the Outlook application, the processing device 110 correspondingly detects that the type of the current application is a mailbox; when the user places the cursor in the browser address bar, the processing device 110 correspondingly detects the current input box.
  • the attribute information is a URL input box.
  • the word segmentation data is filtered according to the association information through S282, and the filtered word segmentation data is displayed.
  • the processing device 110 divides the text information "Bitcoin latest news www.****.com"
  • it can obtain the word segmentation data "Bitcoin”, “Latest”, “Message”, “www.* ***.com”
  • adjust the display order of each word segmentation data according to the method for determining the display priority of the word segmentation data for example, after performing a hot analysis on the word segmentation data according to the current hot word or hot topic, determine the display order of the word segmentation data in order "Bitcoin", "www.****.com", "Latest", "Message”; when the user switches to the Outlook application, the processing device 110 obtains that the type of Outlook is a mailbox application, then Filter "Bitcoin”, "Latest” and "Message” to display only the word segmentation data "www.****.com”.
  • the display order of the word segmentation data can also be adjusted according to the associated information through S283.
  • the processing device 110 may analyze the word segmentation data to determine the degree of matching between the word segmentation data and the related information, and determine the display priority of the word segmentation data according to the matching degree, so that the higher the degree of matching, the display priority of the word segmentation data The higher, the word segmentation data that is closer to the related information is displayed to the user first, so that the user can quickly select the required word segmentation data.
  • the display priority of the word segmentation data "www.****.com” in the above example is adjusted to the highest, and the display order of the adjusted word segmentation data is "www.****.com” and "Bitcoin” ,”latest news”.
  • the clipboard can also store historical text information copied/pasted by the user in different time periods, and the longer the interval, the user selects the participle data The smaller the probability is, and it is obviously meaningless to display the word segmentation data with a longer interval to the user, and it may also disturb the user's normal input and reading. Therefore, in order to help the user quickly exclude the word segmentation data that the user is unlikely to select, the word segmentation data that the user needs most are presented to the user first, so as to improve the user's efficiency in obtaining information, and the following operations can also be performed:
  • the interval time from copying/cutting text information to switching the application is calculated through S2841; then S2842 is used, and when the interval time is less than a preset threshold, the word segmentation data is displayed .
  • the processing device 110 may correspondingly obtain the time stamp of the user's execution of the operation, which is recorded as the first time, and is divided based on the same text information
  • the obtained word segmentation data all correspond to the same first time, and the word segmentation data obtained by segmentation based on different text information can correspond to different first times;
  • the processing device 110 can obtain the time when the user performs the switching operation
  • the stamp is recorded as the second time, and then the processing device 110 calculates the time interval between the second time and the first time corresponding to each word segmentation data, and filters the word segmentation data whose time interval is less than the preset threshold, and displays the filtered word segmentation data to user.
  • the user can also merge two or more word segmentation data into one word segmentation data according to their own needs. For example, the user can sequentially select the word segmentation data to be merged, and the processing device 110 The word segmentation data is merged in the selected order. For example, the user can also drag a word segmentation data to the front or back of another word segmentation data, or between any two characters in the word segmentation data. Where the dragged participle data stays, the two participle data are merged, so that the editing of the participle data is more flexible, and it is convenient for the user to obtain the participle data that the user needs according to their actual needs.
  • the user wants to obtain further information related to Liu Guoliang's network commentary .
  • the user can click the word segmentation data "Liu Guoliang” and “Network commentary” in sequence, or drag the word segmentation data "Network commentary” behind the word segmentation data “Liu Guoliang”, or drag the word segmentation data "Liu Guoliang” to the word segmentation data "Network In front of the commentary, to obtain the combined word segmentation data "Liu Guoliang network commentary", the user can directly select the word segmentation data to obtain the recommendation information associated with the word segmentation data, and can also send the word segmentation data to other users or paste it into the corresponding In the input area.
  • the user can select the corresponding word segmentation data by performing operations such as clicking, double-clicking, long-pressing, sliding up, sliding down, sliding left, or sliding right through the mouse, touch pad, and touch screen; the user can also input voice through the voice input device 130 Information, the voice analysis device recognizes and parses and generates corresponding voice commands to select the corresponding word segmentation data.
  • the processing device 110 can also detect specific operations performed on the word segmentation data by the user, and perform different processing on the word segmentation data according to different operations performed by the user. Referring to the flowchart of the information pushing method shown in FIG. 6, specifically including:
  • the processing device 110 displays the recommendation information associated with the word segmentation data; S32.
  • the processing device 110 divides the word segmentation The data is pasted into the current input area.
  • the first preset operation and the second preset operation can be distinguished from any operation performed by the user to perform the operation of combining word segmentation data.
  • the first preset operation can be configured as a right slide operation
  • the second preset operation can be configured as a click, Double-click or slide-up operation.
  • This process fully considers that users may have different needs when copying text information, so as to provide users with more convenient and fast services, help users quickly enter or quickly obtain associated recommendation information, especially when the user is working with other
  • the user can conveniently and quickly forward different chat content to the corresponding user through the information push system, and can also instantly understand the topics discussed by other users, effectively helping the user to better participate in the chat.
  • the user received the chat message "How to invest in blockchain” sent by user A during group chat, and then user B sent a chat message "You can refer to these two www.qkl**1.com, "www.qkl**2.com”, users want to know more about other information about the blockchain, they can copy the chat information sent by users A and B to get the word segmentation data "blockchain", "www.qkl* *1.com”, “www.qkl**2.com”, “how”, “investment” and presented to the user, and then the user performs a right slide operation on the word segmentation data "blockchain” to obtain the association with the blockchain Recommended information A, and swipe right to "www.qkl**1.com” to get the associated recommended information B.
  • the user can meet the multiple needs of the user by simply sliding or clicking, helping the user to obtain relevant information and share information conveniently and quickly, and the user only needs to copy the text information Copying once can meet the user's subsequent multi-dimensional needs.
  • the method of the present invention can greatly improve the efficiency of users in obtaining information and sharing information.
  • the processing device 110 retrieves the selected word segmentation data through S4, based on at least one of the context information associated with the text information, the user’s historical chat record, or the user’s portrait, and retrieves the search results Perform filtering to obtain recommendation information associated with the selected word segmentation data.
  • step S4 is further explained below in conjunction with FIG. 7.
  • S41 is executed, based on at least one of the context information associated with the text information, the user's historical chat record, or the user's portrait, matching the associated database, and searching the selected word segmentation data based on the associated database.
  • the database may be a cloud database or a local database, or may be partially located in the cloud and partially located locally.
  • the data stored in the database can be crawled in various websites, applications or knowledge bases by the data crawling device, and then the crawled data is stored in the database according to their respective categories.
  • the database can be classified according to the data type, for example, the database is divided into a text database, a picture database, an audio database, a video database, etc.;
  • the database can also be classified according to the category corresponding to the data source.
  • the data crawled from shopping websites such as Amazon, Taobao, JD.com, etc. are stored in the shopping database, which will be from Toutiao, Tencent News,
  • the data crawled in Weibo is stored in the information database.
  • various databases can be further classified according to different data sources.
  • shopping databases include Taobao database, Jingdong database, and Amazon database.
  • the database may not be classified, but the acquired data may be identified according to the data source. For example, all data crawled from Taobao will be identified as "Taobao” and crawled from Weibo The data is identified as "Weibo", and the crawled data can be further identified according to the category of the data source.
  • the processing device 110 matches the associated data identifier according to at least one of the context information associated with the text information, the user's historical chat record, or the user's portrait, and filters the retrieval results based on the associated data identifier to obtain the word segmentation Recommendation information associated with the data.
  • the selected word segmentation data can also be directly retrieved through the data interface provided by the corresponding website or application, and the processing device 110 can identify or name the data interface according to the application or website corresponding to the data interface
  • the data interface corresponding to Taobao is named or identified as "Taobao”
  • the processing device 110 can also identify or name the data interface according to the category to which the application or website belongs, for example, "Taobao", “Jingdong” and " The data interfaces corresponding to "Amazon” are identified or named "shopping”, and then the processing device 110 matches the associated website or application according to at least one of the context information associated with the text information, the user's historical chat record, or the user's portrait Program, and retrieve the selected word segmentation data according to the data interface provided by the associated website or associated application program, and filter the search results to obtain recommendation information associated with the selected word segmentation data.
  • the processing device 110 may perform semantic analysis on the selected word segmentation data according to the context information associated with the text information, and retrieve the selected word segmentation data according to the semantic analysis result.
  • using different databases to retrieve the word segmentation data may obtain different results.
  • the word segmentation data "basketball”
  • the basketball commodity information is obtained, but through the information database The information obtained during the search is about the basketball game.
  • the context information associated with the text information to perform semantic analysis on the selected word segmentation data, determine the data category to which the word segmentation data belongs, and filter the related data content according to the data category. Furthermore, the word segmentation data is retrieved based on the content of the related data.
  • the processing device 110 can obtain the context information associated with the text information through the data interface provided by the application program; it can also obtain the context information associated with the text information through the data interface provided by the system; the processing device 110 can also detect the screen To obtain the context information associated with the text information. Specifically, the processing device 110 may intercept the screen when the user performs copy/cut operations on the text information, and then recognize the text information in the screen through the graphic recognition technology, and Context information associated with text information is extracted.
  • deep learning algorithms can be used for semantic analysis, such as part-of-speech tagging, word segmentation, entity naming recognition and purpose extraction of context information through neural networks to obtain user needs, and then determine the data category to which the word segmentation data belongs.
  • the data category can be divided into text category, picture category, audio category and video category, etc.
  • the data category can be further divided into shopping sub categories according to the category corresponding to the data crawling source Category, information sub-category, etc.
  • the sub-category data can be further divided, for example, the shopping sub-category is further divided into Taobao, Jingdong, Amazon and so on.
  • the data category may correspond to the classification of the database.
  • the processing device 110 may match the database corresponding to the category according to the data category to which the word segmentation data belongs, and retrieve the word segmentation data based on the database.
  • the processing device 110 can know that the blue and white porcelain belongs to by analyzing the context information
  • the processing device 110 may retrieve the word segmentation data "blue and white porcelain” based on the audio database, thereby providing the song "blue and white porcelain.mp3" to the user.
  • the data category may also correspond to the data identifier, and the processing device 110 may determine the data identifier corresponding to the category according to the data category to which the word segmentation data belongs, and extract the data marked with the data identifier, and then The word segmentation data is retrieved based on the extracted data.
  • the data category may also correspond to the name/identification of the data interface, and the processing device 110 may determine the name/identity of the data interface corresponding to the category according to the data category to which the word segmentation data belongs, and based on the data interface retrieve the word segmentation data.
  • the processing device 110 may also determine user habits, preferences or points of interest according to at least one of the user's historical chat records or user portraits, and according to at least one pair of user habits, preferences or points of interest The selected word segmentation data is searched.
  • the processing device 110 can obtain the user's historical chat information through the chat software or the data interface provided by the system, and then analyze the historical chat information to determine user habits, preferences, points of interest, etc. .
  • the processing device 110 can analyze the user according to a series of operation records generated by the user using the terminal, construct a series of tags suitable for describing the user, and store the series of tags in the user portrait, specifically, according to the user Browsing web pages, data downloaded by the user, information actively entered or searched by the user, and GPS information of the user's device, etc., determine the user's interests and preferences; you can also determine the application that the user is used to based on the user's record of the application, and furthermore Classify the applications and determine the applications that users are used to in each category.
  • the shopping application that users are used to is JD.com
  • the information application that users are used to is Tencent News
  • the browser that users are used to. UC browser the processing device 110 can analyze the user according to a series of operation records generated by the user using the terminal, construct a series of tags suitable for describing the user, and store the series of tags in the user portrait, specifically, according to the user Browsing web pages, data downloaded by the user, information actively entered
  • the processing device 110 retrieves the weather information of Shanghai and feeds it back to the user; for example, if the user's preference includes property information, then the user When the word segmentation data "Shanghai" is selected, the processing device 110 retrieves the housing price dynamics in Shanghai and feeds them back to the user; for another example, the application frequently used by the user is Weibo, and the user's interest points include real estate, when the user selects the word segmentation data " "Shanghai", the processing device 110 retrieves the information about the Shanghai property in Weibo and feeds it back to the user.
  • the processing device 110 may first perform semantic analysis on the selected word segmentation data according to the context information associated with the text information to determine the data category to which the word segmentation data belongs, and based on at least one of the user’s historical chat records or user portraits, The subordinate categories in the data category are screened, and the word segmentation data is retrieved based on the subordinate data categories after screening.
  • the processing device 110 can feedback the song blue and white porcelain in the cool dog to the user .
  • processing device 110 may also determine the data category to which the word segmentation data belongs according to the type of word segmentation data, filter the related data content according to the data category, and then retrieve the word segmentation data according to the related data content.
  • the types of word segmentation data may be, for example, URL addresses, email addresses, telephone numbers, and so on.
  • the word segmentation data when the word segmentation data is obtained as a URL address, it is determined that the data category to which the word segmentation data belongs is a browser, and then a database classified as a browser or a data interface identified as a browser is filtered according to the data category. Through the database or data The interface retrieves the URL address.
  • the processing device 110 can also combine the type of word segmentation data and the user portrait to retrieve the analysis data.
  • the word segmentation data is obtained as a URL address
  • the browser that the user is used to record in the user portrait is the UC browser. Then directly search the URL address through the database or data interface corresponding to the UC browser to obtain the content in the URL address.
  • the search results are filtered according to the user portrait.
  • the processing device 110 may filter the search results according to one or more tags in the user portrait.
  • the processing device 110 retrieves several search results about the basketball game through the database or data interface corresponding to Tencent News, and according to the user portrait, it can be seen that the user's points of interest include “NBA” and "Kobe” Then, the processing device 110 may filter the information associated with "NBA” and "Kobe” in the search results, and present the search results matching the user's points of interest to the user.
  • the recommendation information can be displayed in the form of a card near the word segmentation data, and the user can directly obtain the recommendation information by reading the card content without opening the corresponding application.
  • the recommendation information may be displayed in the segmentation data in the form of a card Right. The user can directly read the information in the card to get the recommended content.
  • the recommendation information may be displayed in the form of a card Word segmentation data on the right.
  • the user can also perform corresponding operations, such as double-click or long-press to enlarge the card, or display the card in full screen, double-click or long-press again to restore the original card size.
  • corresponding operations such as double-click or long-press to enlarge the card, or display the card in full screen, double-click or long-press again to restore the original card size.
  • the user can also slide up and down to select the previous piece of recommended information or the next piece of recommended information.
  • the recommendation information obtained by the processing device 110 may contain a large amount of information. The user needs to spend a lot of time to read the original content of the web page and find the information that he needs or is interested in. In order to further improve the user's access to information For efficiency, the processing device 110 can also intercept the content associated with the selected word segmentation data in the web page, and present the intercepted content as recommendation information to the user.
  • the processing device 110 may search the word segmentation data in the original text of the web page, obtain the content associated with the word segmentation data, and intercept the part of the content as recommendation information to present to the user, thereby saving the user's reading time.
  • the user needs to read the full text, he can perform corresponding operations, such as double-clicking or long-pressing the recommended information, to obtain the original content of the webpage of the recommended information.
  • execute S6 paste the selected recommendation information into the current input area according to the user's operation on the recommendation information; or push and display the secondary recommendation information associated with the selected recommendation information.
  • the processing device 110 pastes the recommendation information into the current input area, for example, pastes the recommendation information card into the input box where the cursor is, or converts the recommendation information card It is a picture format, and then paste it into the current input box, or extract the text information in the recommended information and paste it into the current input box.
  • the third preset operation may be, for example, a click operation or other arbitrary setting operations.
  • the processing device 110 When the user performs the fourth preset operation on the recommendation information, the processing device 110 further recommends the secondary recommendation information according to the relevance of the recommendation information and other webpage content, and presents the secondary recommendation information to the user. Wherein, the processing device 110 may use webpage content with similar topics, similar categories, similar content, or other relevance as the second-level recommendation information.
  • the fourth preset operation may be, for example, a right-slide operation or other arbitrary setting operations.
  • the selected word segmentation data can also be pasted into the current input area through S7 according to the operation performed by the user on the word segmentation data.
  • the current input area can be the input box where the cursor is in the current page, or the input box of the application after the user switches the application, or the input area of the editing document, such as a word document; wherein, the operation performed by the user It can be single-click, double-click or slide-up operation.
  • processing device 110 may paste the selected word segmentation data after the input content in the current input area, or may replace the selected word segmentation data with the input content in the current input area.
  • the type of the word segmentation data can also be detected through S8 to determine whether the type of the word segmentation data is a preset type; then through S9, when the word segmentation data When the type of is a preset type, call a local application that matches the type of word segmentation data to perform a preset operation on the word segmentation data or display a function option corresponding to the type of word segmentation data.
  • the preset type can be a phone number, email address, web address, plain text or other types, etc.
  • the local application corresponding to the phone number can be an application such as a phone book, toll-free phone, etc.
  • the local application corresponding to the email address can It is a mailbox application.
  • the local application corresponding to the URL can be a browser application.
  • the local application corresponding to the plain text can be the application currently being used by the user. For example, the current application can be obtained by detecting the application list process.
  • users can also customize the type and set the word segmentation data corresponding to the type, and configure the local application corresponding to the type.
  • the local application can determine the preset operation according to the type of word segmentation data, for example, directly start the corresponding local application and fill the corresponding local application with the phone number, email address, web address, or plain text In the input area, which greatly saves the time for users to input information, simplifies the complexity of user operations, and improves the processing efficiency of word segmentation data.
  • the local application can also determine the function options that need to be displayed according to the type of the word segmentation data. For example, for a phone number, when the user selects the phone number, the phone number can be displayed near the word segmentation data.
  • the function options for example, can be "Call this number”, "Send SMS to this number” or "Store this phone number”, etc.
  • the user can select the corresponding function option according to his own needs, such as "dial the number", the local application will automatically start and directly perform the operation of dialing the phone number. This can greatly simplify user operations, help users quickly and quickly perform functions related to word segmentation data, and improve processing efficiency.

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Abstract

一种基于剪贴板进行信息推送的方法、装置和终端设备，其中，所述方法包括：获取复制/剪切到剪贴板中的文本信息；将所述文本信息切分，获得至少一个分词数据，并显示所述分词数据，所述分词数据为文本信息的子集；检测用户选择的分词数据；根据与所述文本信息关联的上下文信息、用户历史聊天记录或者用户画像中的至少一种，对选择的分词数据进行检索，并对检索结果进行过滤，获得与选择的分词数据相关联的推荐信息；显示所述推荐信息。相较于现有技术，本发明各实施方式节省了信息的获取时间，减少了用户操作，提高了用户信息的获取效率。

Description

基于剪贴板进行信息推送的方法、系统及终端设备 技术领域
本发明实施例涉及信息处理技术，尤其涉及基于剪贴板进行信息推送的方法、系统及终端设备。
背景技术
日常生活中，用户在聊天或者浏览网页时常常会有进一步获取信息的需求，比如，用户在聊天时碰到感兴趣的内容或者热门话题，用户想了解更多的信息以便参与到聊天中；又或者，用户在浏览微博时看到其他用户使用的产品，用户想要购买该产品。
针对用户的各种信息获取需求，目前普遍的做法是：用户根据想要获取的信息，手动打开相应的应用程序，在应用程序的搜索框中输入关键字进行检索，然后在若干检索结果中筛选出自己想要的内容。
另外，现有技术还提供了基于用户复制的内容进行搜索的方案，以微信为例，用户可以在公众号推文页面执行长按操作来选中复制功能，然后截选需要检索的关键字，在给出的功能选项中选择“搜索”选项，再跳转到应用程序选择页面选择相应的应用程序对关键字进行检索。
然而，这两种方法都比较耗费用户时间，而且还会增加用户操作，使得用户获取信息的效率较低。
进一步来说，当用户想要检索的信息比较多时，用户需要在检索完上一个关键字后，在应用程序中手动输入下一关键字来继续检索，根据检索需求的不同，用户还需要切换到不同的应用程序中对关键字进行检索；又或者，用户在检索完上一个关键字后，返回到微信页面，按照上述第二个方案中的方法选择下一个关键字继续检索，直到检索完所有的关键字。可以看出，一旦用户想要检索的信息比较多时，现有技术的方案就会大量消耗用户的时间，并且严重降低用户获取信息的效率。
发明内容
本发明实施例提供基于剪贴板进行信息推送的方法、系统及终端设备，以实现节省用户信息获取时间，减少用户操作，提高用户信息获取效率的目的。
根据本发明的一个方面，提供一种基于剪贴板进行信息推送方法、系统和 终端设备，其中，所述方法包括：获取复制/剪切到剪贴板中的文本信息；将所述文本信息切分，获得至少一个分词数据，并显示所述分词数据，所述分词数据为文本信息的子集；检测用户选择的分词数据；根据与所述文本信息关联的上下文信息、用户历史聊天记录或者用户画像中的至少一种，对选择的分词数据进行检索，并对检索结果进行过滤，获得与选择的分词数据相关联的推荐信息；显示所述推荐信息。
根据本发明的另一个方面，还提供一种基于剪贴板的信息推送系统，，其中，该系统包括：处理设备、存储设备、输入设备以及显示设备；所述输入设备，适于检测用户执行的输入操作；其中，所述输入操作至少包括复制/剪切操作，以及对分词数据的选择；所述处理设备，适于执行切分操作以及推送操作；其中，所述切分操作至少包括：根据所述输入设备获取的复制/剪切操作，获取复制/剪切的文本信息；将所述文本信息切分，获得至少一个分词数据；将所述分词数据发送至显示设备；其中，所述分词数据为所述文本信息的子集；以及所述推送操作至少包括：根据所述输入设备获取的用户操作，获取所选择的分词数据；根据与所述文本信息关联的上下文信息、用户历史聊天记录或者用户画像中的至少一种，对所选择的分词数据进行检索，并对检索结果进行过滤，获得与所述选择的分词数据相关联的推荐信息；将所述推荐信息发送至所述显示设备；所述存储设备，包括剪贴板以及包含推荐信息的数据库；其中，所述剪贴板适于保存所述复制/剪贴的文本信息；所述显示设备，适于显示文本信息，并根据处理设备的操作显示对应的分词数据和/或推荐信息。
根据本发明的另一个方面，还提供一种终端设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，其中，该处理器执行的程序包括本申请所公开的任一种方法。
通过本发明的各种实施方式，该基于剪贴板进行的信息推送机制可配置为获得用户曾复制或剪切的文本信息，通过将该文本信息切分为至少一个分词数据，并根据用户所选择的分词数据，以及与该文本信息关联的上下文信息或者相关的用户信息，进而进行检索过滤，获得相关联的推荐信息并提示给用户，从而使得用户能够通过该信息推送系统快速获得与分词数据关联的推荐 信息节省了信息的获取时间，减少了多次反复操作，提高了信息的获取效率。
附图说明
图1为本发明某实施例提供的基于剪贴板的信息推送系统的框架示意图；
图2为本发明某实施例提供的基于剪贴板的信息推送方法的流程示意图；
图3为图2所示步骤S2的某实施例提供的流程示意图；
图4a-d为本发明某实施例提供的基于剪贴板的信息存储和推送的界面示意图；
图5a-b为图3所示步骤S28的某实施例提供的流程示意图；
图6为图2所示步骤S3的某实施例提供的流程示意图；
图7为图2所示步骤S4的某实施例提供的流程示意图；
图8a-b为图2所示步骤S5的某实施例提供的界面示意图；
图9为本发明另一种某实施例提供的基于剪贴板的信息推送方法的流程示意图；
图10为本发明又一种某实施例提供的基于剪贴板的信息推送方法的流程示意图。
具体实施方式
为使本发明的目的、技术方案和优点更加清楚，下面结合附图对本发明作进一步的详细描述。
附图中的流程图和框图，图示了按照本发明各种实施例的装置、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上，流程图或框图中的每个方框可以代表一个模块、程序段或代码的一部分，所述模块、程序段或代码的一部分包含一个或多个用于实现预定的逻辑功能的可执行指令。也应当注意，框图和/或流程图中的每个方框以及框图和/或流程图中的方框的组合，可以用执行规定的功能或操作的专用的基于硬件的系统来实现，或者可以用专用硬件与计算机指令的组合来实现。
在本文中，诸如左和右，上和下，前和后，第一和第二之类的关系术语仅仅用来区分一个实体或动作与另一个实体或动作，而不一定要求或暗示这种实体或动作之间的任何实际的这种关系或顺序。术语“包括”、“包含”或任何其他变体旨在涵盖非排他性的包含，由此使得包括一系列要素的过程、方法、 物品或者设备不仅包含这些要素，而且还包含没有明确列出的其他要素，或者为这种过程、方法、物品或者设备所固有的要素。
图1示出示例性基于剪贴板的信息推送系统的框图。根据某些实施例，信息推送系统可以是包含显示屏的移动终端，例如移动手机、智能手机、PDA或平板电脑，也可以是其他可与互联网进行交互的电子设备，例如相机、穿戴电子设备、车载导航设备、设置在车站或学校等公共场所的电子交互终端。
该信息推送系统可通过宽带，例如ADSL、VDSL、光纤、无线、有线电视、卫星等方式接入网络，也可通过窄带，例如电话拨号接入、GPRS、2G、3G等方式接入互联网，或者也可通过CDMA、2G、3G、4G等技术接入电信网络。
根据某些实施例，该信息推送系统可被配置为记录用户复制/剪切的文本信息，并对该文本信息切分为至少一个分词数据，检测用户的选择，确定用户选择的分词数据，然后根据与文本信息关联的上下文信息，或者与用户相关联的信息，比如用户画像或者用户的历史聊天记录，来对选择的分析数据进行检索过滤，获得相关联的推荐信息，使得用户能够通过该信息推送系统快速获得与分词数据关联的信息。
根据本发明的实施例，剪贴板可以是系统内存中的一块区域，适于存放用户复制或者剪切的信息。信息推送系统还可以对剪贴板进行配置，将用户历史复制或者剪切的信息长期存储到剪贴板中，以供用户随时进行查看，或对剪贴板中的记录进行编辑，以保存需要的文本信息。在某些实施例中，信息推送系统还可对用户复制或者剪切到剪贴板中的文本信息进行检测，对相同的文本信息进行次数标记，并在剪贴板中将该次数标记信息显示在与该文本信息相应的位置。在其他实施例中，信息推送系统还可根据次数标记信息确定剪贴板中相应文本信息的显示优先级，按照该显示优先级对剪贴板中的文本信息进行排序。在某些实施例中，剪贴板也可以根据需要，被配置为仅存储用户临时复制或者剪切的信息，当有新的数据传入时，就覆盖掉原来的信息。
举例来说，用户在工作中经常对邮箱地址进行复制/剪切，则信息推送系统对用户复制或者剪切的文本信息进行次数标记，确定“邮箱地址1”的复制/剪切次数最高，“邮箱地址2”的复制/剪切次数次之，其他文本信息的复制/剪切次数较少，则可确定邮箱地址1的显示优先级高于邮箱地址2，邮箱地址2的显示优先级高于其他文本信息，然后根据该显示优先级对剪贴板中的文本信息进行排序。
进一步来说，信息推送系统通过设置作为存储设备的剪贴板，根据用户的 复制/剪切操作，将用户在任意应用程序中所复制/剪切的内容存储到至该剪贴板中；并且，通过剪贴板相应获取该文本信息并进而自动执行切分以及实现个性化的信息推荐，从而使得该信息推送系统能够跨应用地获取用户在不同应用中收集的文本信息，并以此为基础，实现对分词数据的获取和推荐信息的检索，提高信息推送系统的通用性。值得一提的是，该信息推送系统在移动终端设备尤为重要。目前常用的移动终端设备中，由于各个应用软件相互独立，而应用软件和系统软件大多来自各不相同的开发商，用户在不同应用之间切换操作时，在应用软件中所剪切的文本通常无法被记忆并应用至其它应用软件。此外，即便是系统级的应用软件，其不仅需要用户手工通过进行额外的粘贴等操作以实现剪切或复制的文本信息的保存，并且通常该类应用无法实现自动根据所剪贴的内容实现智能切分以及推荐信息的检索和推送。而本申请的某些实施例，能够实现主动对剪切或复制的文本信息进行存储和智能切分，并且能够使得所存储的文本信息、切分的分词数据和其对应的推荐信息，能够在与用户执行复制/剪切操作相同或不同的应用之间被调用，从而使得用户能够便利地在多个应用之间通过复制/剪贴操作获取到关联的推荐信息，节省了信息的获取时间，减少了多次反复操作，提高了信息的获取效率。
根据本发明的实施例，术语“文本信息”可以是不包含图片的字符，包括任意语言对应的文字、字母、数字或者任意类型的符号，其中符号例如可以是标点符号、运算符号、表情符号、几何符号或者其他类型的符号等，文本信息可以是纯文字、纯字母、纯数字、纯符号或者上述任意信息类型的组合，比如网址、邮件地址等。另外，“文本信息”可以是用户在任意应用场景中复制/剪切的信息，比如，用户在聊天场景中复制/剪切的聊天信息，又比如，用户在新闻类应用程序中复制的时事新闻，再比如，用户在社区或者论坛中复制/剪切的URL(Uniform Resource Locator，统一资源定位符)地址。
根据本发明的实施例，术语“分词数据”为对文本信息按照一定切分规则进行切分处理后的一个子集，分词数据的长度小于文本信息的长度。
根据本发明的实施例，术语“用户画像”是用来描述用户的一些列标签，通过主动或者被动地收集用户在互联网留下的种种数据，并进一步对这些数据进行分析、加工，从而形成描述用户的标签。“用户画像”被宽泛地使用以包括以下至少一种:用户的个人信息,例如用户的年龄、性别、身高、体重、国籍、籍贯、常住地、学历、职业、技能、特长、兴趣爱好等；与用户设备相关的信息，例如用户设备的实时位置信息，用户设备的型号，用户设备使用的系 统语言或者用户设备的其他配置信息等；用户历史复制/剪切习惯，例如，用户经常复制文本+URL地址，文本+电话号码，或者文本+邮箱地址等；用户历史输入习惯，例如用户输入网址时习惯只输入域名，又比如，用户聊天时习惯不加主语；“用户画像”还可包括用户习惯使用的应用程序，比如，用户习惯使用的购物类应用程序有亚马逊和京东，用户习惯使用的资讯阅读类应用程序是今日头条和新浪新闻，用户习惯使用的通讯社交类应用程序是微博、微信和Instagram等等。
根据本发明的实施例，术语“推荐信息”可以包括以下至少一种，文本信息、图片信息、URL地址、音频、视频以及安装包等等。
参考图1，信息推送系统可以包括处理设备110、存储设备120、输入设备130以及显示设备140。其中，处理器可以是中央处理单元(“CPU”)或图形处理单元(“GPU”)，具体来说处理设备110可以包括一个或者多个印刷电路板或微处理模块芯片，执行计算机程序指令序列以执行将在下文中更详细解释的各种方法。
在某些实施例中，处理设备110可配置为通过输入设备130获取复制/剪切到剪贴板中的文本信息，并对文本信息进行切分，根据用户对分词数据的操作，将用户选择的分词数据粘贴到当前输入区，或者根据与文本信息关联的上下文信息、用户历史聊天记录或者用户画像中的一种或者其任意组合，在存储设备120中进行检索，获得与分词数据关联的推荐信息，然后将粘贴到当前输入区的分词数据或者检索得到的推荐信息通过显示设备120予以呈现。
存储设备120可包括随机存取存储器(“RAM”)和只读存储器(“ROM”)中的一种或多种。计算机程序指令可从ROM或任何其它合适的存储器位置访问和读取，并且被加载到RAM中以供处理设备110执行。例如，存储设备120可存储一个或多个软件应用。存储在存储设备120中的软件应用可包括用于普通计算机系统以及用于软件控制的设备的操作系统。此外，存储设备120可存储整个软件应用或者存储软件应用中的可由处理设备110执行的仅仅一部分。例如，存储设备120可存储可由处理设备110执行的信息推送软件并且执行信息推送方法。
根据某实施例，存储设备120可包括剪贴板以及包含推荐信息的数据库，数据库可以是本地数据库，也可以是云端数据库，还可以部分位于本地，部分位于云端。在某些实施例中，存储设备120中还存储有用户历史聊天信息以及与用户画像关联的数据，比如，用户的历史输入记录、用户历史复制/剪切记录、 用户使用应用程序的记录或者用户的其他操作记录等等。
在某些实施例中，输入设备130和显示设备140可通过适当的接口电路耦合至处理设备110。在某些实施例中，输入设备130可以是鼠标、键盘、触摸板或者触摸屏，适于检测用户执行的输入操作，比如用户通过鼠标选中某段文本信息，并通过键盘的快捷键进行复制或者剪切操作，又比如，用户通过触摸板或者触摸屏执行单击、双击、长按、上滑、下滑、左滑或者右滑等操作。在某些实施例中，输入设备130也可以包括感应输入设备130，例如输入设备130可为语音输入设备130和语音解析设备，其中，用户通过语音输入设备130进行语音输入，语音解析设备检测到存在用户的语音输入时，对用户输入的语音内容进行识别和指令解析，识别结果可以为执行与该输入语音对应的操作信息，比如，复制操作、剪切操作、选择操作等。在某些实施例中，输入设备130也可包括某些功能按键，用户可通过这些功能按键发起由信息推送系统执行的某些过程，或以其它方式与信息推送系统交互。
显示设备140可包括向用户显示文本或图形的一个或多个显示屏。例如，显示设备140可显示GUI。
在某些实施例中，信息推送系统还包括网络接口150，网络接口150可提供通信连接，使得信息推送系统可通过网络接口150连接到云端160。
下面结合相应的附图对基于剪贴板进行信息推送的方法进一步解释。
图2示出本发明某一实施例提供的信息推送方法流程图，包括：
S1：获取复制/剪切到剪贴板中的文本信息。
其中，可以通过检测用户的操作来获取相应的文本信息。具体来说，当输入设备130检测到用户执行复制/剪切操作时，处理设备110相应获取用户复制/剪切的信息，比如，用户在某聊天应用程序中与其他用户聊天时接收到了其他用户发送的比特币信息，用户想进一步了解比特币，并对“比特币最新消息www.****.com”执行了复制操作，此时处理设备110获取用户复制的“比特币最新消息www.****.com”；又比如，用户在某新闻类应用程序中浏览新闻时看到了某地的房价信息，用户想进一步了解该地的房价动态，并对“**市房价走势”执行了复制操作，此时处理设备110获取用户复制的“**市房价走势”。
可以看出，用户可以在任意应用程序中对相应的信息执行复制/剪切操作，当用户执行复制/剪切操作时，信息推送系统相应获取复制/剪切到剪贴板中的文本信息，经切分、用户选择分词数据等操作后获得相应的推荐信息， 也就是说，信息推送系统可以在任意应用程序中为用户推荐相应的推荐信息，从而实现跨应用信息推荐，方便用户快捷地获得推荐信息，帮助用户快速阅读或者聊天。
处理设备110也可以在信息推送系统运行的任意时刻直接获取剪贴板中存储的历史粘贴信息，比如，当信息推送系统启动时，处理设备110按照相应获取规则获取剪贴板中的信息。
在某一实施例中，处理设备110可以获取最后一次复制/剪切到剪贴板中的文本信息，比如，用户在浏览微博时先后复制了“霍金”和“时间简史”，则处理设备110获取用户最后一次复制的信息“时间简史”。
在另一实施例中，处理设备110也可以获取最近预设次数内复制/剪切到剪贴板中的所有文本信息，比如，用户在浏览微博时复制了话题“房产进行时”，然后在阅读时事新闻时又先后复制了“房产调控政策”和“房贷利率排名”，假设预设次数为2次，则处理设备110获取最近2次复制的信息“房产调控政策”和“房贷利率排名”。
在其他实施例中，处理设备110还可以获取预设时间内复制/剪切到剪贴板中的所有文本信息，比如，处理设备110仅获取24小时内复制/剪切到剪贴板中的所有文本信息。进一步来说，随着时间的更新以及用户复制/剪切内容的更新，处理设备110获取的文本信息也可以实时更新。
根据某一实施例，处理设备110还可以获取用户在剪贴板中主动选择的文本信息，具体来说，用户可以通过输入设备130打开剪贴板，剪贴板相应呈现用户历史复制/剪切的信息，当用户在剪贴板中选择某一历史信息时，处理设备110相应获取用户选择的信息。
S2：将所述文本信息切分，获得至少一个分词数据，并显示所述分词数据，所述分词数据为文本信息的子集。
图3示出步骤S2的具体方法流程图，参见图3，对文本信息进行切分包括：S21、按照相应的分词算法对所述文本信息进行切分。
其中，分词算法可以包括基于字符串匹配的分词方法，即按照一定的策略将待分析的文本信息与机器词典中的词条进行匹配，如果在词典中可以找到某个字符串，则匹配成功，即识别出一个分词数据。分词算法还包括基于理解的分词方法，在切分时同时进行句法和语义分析，针对不同的语言，可采用不同的句法和语义分析规则对文本信息进行切分。举例来说，当获取的 文本信息为“篮球明星姚明”，则可对该文本信息进行句法和语义分析后确定该文本信息由三个名词“篮球”、“明星”以及“姚明”构成，因此可按照词性将该文本信息切分为三个分词数据“篮球”、“明星”以及“姚明”。又比如，当获取的文本信息为“Basketball star Yao Ming”则可直接根据空格以及词性将该文本信息切分为“Basketball”、“star”以及“Yao Ming”。
分词算法还可以包括基于统计的分词方法，可以通过确定相邻字共同出现的频率来确定成词的可信度，进而对文本信息进行切分，仍以文本信息“篮球明星姚明”为例，当“篮球”与“明星”共同出现的频率超过预设频率时，此时可将“篮球”与“明星”合并作为一个分词数据，如此得到分词数据“篮球明星”与“姚明”。在其他实施例中，分词算法还可以通过机器学习模型来对文本信息进行切分。
进一步来说，还可根据分词数据的类型来对文本信息进行切分，其中，分词数据的类型可以包括URL地址、邮箱地址、电话号码等。
例如，对于剪贴板中存储的历史信息“王*联系方式：183****0000，wang***@126.com，https://weibo.com/**/**.com&****”，当用户进入剪贴板并选择该信息时，处理设备相应获取该信息，并将该信息切分为“王某联系方式”、“183****0000”、“wang***@126.com”、“https://weibo.com/**/**.com&****”，然后显示在屏幕显示界面中，具体可以如图4a所示。
继续参见图3，对文本信息进行切分还可包括：S22、根据用户历史粘贴记录或者历史输入记录获取用户切分习惯；然后通过S23、根据用户切分习惯对所述文本信息进行切分。
其中，处理设备110可以通过读取日志信息来获取用户历史粘贴记录或者历史输入记录，经统计分析后获得用户的切分习惯。比如，开发人员在工作时常常需要群里发布版本链接信息，或者复制别人发布的版本链接，因此在输入或者粘贴时常常会用到“姓名+链接”或者“链接+姓名”的格式信息，处理设备110在检测到文本信息中包含姓名和链接时，可将“姓名+链接”或者“链接+姓名”作为一个分词数据对文本信息进行切分,以便用户后续对该分词数据进行粘贴，或者转发给其他用户。
根据某一实施例，在获得分词数据之后，还包括S24、根据用户输入习惯对获得的分词数据进行补充编辑。其中，处理设备110可通过对用户历史输入记录来分析用户的输入习惯，比如用户在聊天时常常用“喜欢你”来表 达“我喜欢你”，可知用户聊天时习惯不加自身主语，又比如，用户在输入网址时常常输入“baidu.com”、“sina”，可知用户输入网址时习惯只输入域名或者部分域名，当检测到分词数据“google.com”时，可对其进行补充编辑，形成新的分词数据“www.google.com”。进一步来说，补充编辑后的分词数据可以直接替换原来的分词数据，也可以同时保留原分词数据和新的分词数据，以便用户根据当前需求进行选择。
根据另一实施例，在对分词数据补充编辑时，还可检测文本信息发送者的身份信息，并将该身份信息添加到分词数据中。其中，身份信息可以是该发送者的名称或者昵称等。举例来说，当用户选择了分词数据“131****1111”时，则获取发送该分词数据的发送者的昵称“用户A”，并将“用户A”添加到原来的分词数据“131****1111”中，得到补充编辑后的分词数据“用户A+131****1111”。在其他实施例中，还可对用户选择的分词数据进行检测，当该分词数据的类型为预设类型，比如电话、邮箱等，或者该分词数据符合用户的输入习惯，比如用户习惯输入“姓名+链接”或者“链接+姓名”的格式信息，则对文本信息发送者的身份信息进行检测，并将该身份信息添加到分词数据中。其中，身份信息的添加位置可以按照预设格式进行设定，或者根据用户的输入习惯进行设定或调整。
进一步地，在获得分词数据之后，还可调整分词数据的显示顺序。根据某一实施例，调整分词数据的显示顺序具体可以包括：S25、当获得的分词数据在两个以上时，根据用户画像对获得的分词数据进行匹配分析，并调整显示顺序，使得与用户画像匹配度高的分词数据具有更高的显示优先级。
其中，用户画像中记录着用来描述用户的一些列标签信息，并被宽泛地使用以包括以下至少一种:用户的个人信息,例如用户的年龄、性别、身高、体重、国籍、籍贯、常住地、学历、职业、技能、特长、兴趣爱好、用户习惯、用户偏好等；与用户设备相关的信息，例如用户设备的实时位置信息，用户设备的型号，用户设备使用的系统语言或者用户设备的其他配置信息等。
处理设备110可将分词数据与用户画像中记录的各标签信息进行匹配，确定分词数据与用户画像的匹配度，具体来说，分词数据与用户画像中的标签信息关联性越高，或者与分词数据相匹配的标签信息越多，该分词数据与用户画像的匹配度越高。然后，处理设备110根据分词数据与用户画像的匹配度来确定该分词数据的显示优先级，使得与用户画像匹配度高的分词数据具有更高的 显示优先级，并根据分词数据的显示优先级调整分词数据的显示顺序，以便将与用户关联性最高的分词数据优先提供给用户，方便用户快速选择。
举例来说，参见图4b，用户在浏览新闻时复制了标题“‘*’变网络解说，刘国梁转身这一年”，经切分后获得分词数据“*”、“变”，“网络解说”、“刘国梁”、“转身”、“这一年”，根据用户画像可知，用户经常浏览关于刘国梁的新闻，将用户画像与这些分词数据进行匹配分析，可确定分词数据“刘国梁”与用户画像的匹配度最高，其次是分词数据“*”，然后是分词数据“网络解说”，则将分词数据的显示顺序调整为“刘国梁”、“*”、“网络解说”、“变”、“转身”、“这一年”。
根据某一实施例，处理设备还可以降低无实际意义的分词数据的显示优先级，比如“的”、“吗”、“是”，将这些分词数据靠后显示，或者直接过滤掉这些无实际意义的分词数据。
比如，参见图4c，用户在群聊天时复制了其他用户发送的聊天信息“《亲爱的篮球》是科比投资制作的”，经切分后获得分词数据“《亲爱的篮球》”、“是”、“科比”、“投资制作”、“的”，根据用户画像可知，用户的兴趣爱好中包括打篮球，且用户常常浏览关于NBA的信息，将用户画像与这些分词数据进行匹配分析，可确定分词数据“科比”与用户画像的匹配度最高，然后是分词数据“《亲爱的篮球》”，进一步还可将无实际意义的分词数据“是”和“的”过滤掉，呈现如4c所示的分词数据。
在另一实施例中，调整分词数据的显示顺序还可以包括：S26、当获得的分词数据在两个以上时，根据当前热词或者热门话题对分词数据进行热度分析，并调整显示顺序，使得与当前热词或者热门话题关联的分词数据具有更高的显示优先级。
其中，可以根据大量用户输入关键字的频率来统计热词或者热门话题，并根据关键字被输入的次数确定热词或者热门话题的热度；也可以从第三方网站中直接获取热词/热门话题以及对应的热度，然后分词数据与当前热词/热门话题进行匹配，确定该分词数据的热度，进而根据分词数据的热度调整分词数据的显示顺序。
举例来说，用户复制了其他用户发送的聊天信息“你知道比特币吗？”，经切分后获得分词数据“你”、“知道”、“比特币”、“吗？”，经查询 可知比特币为当前热词，则可将分词数据“比特币”显示顺序调整到最前面。
根据某一实施例，还可根据默认设定规则或者用户设定规则来确定分词数据的显示优先级，进而根据显示优先级来调整分词数据的显示顺序。比如，规定电话显示优先级＞邮箱地址显示优先级＞URL地址显示优先级。
接下来执行S27、显示分词数据。
根据某一实施例，可以通过卡片形式来显示分词数据，参考如图4b-4c所示的屏幕显示界面，分词数据可以按照显示优先级以列表形式呈现在卡片中。
根据另一实施例，还可以通过气泡形式来显示分词数据，参考如图4d所示的屏幕显示界面，每个气泡可以承载一个分词数据，根据分词数据的显示优先级可以确定气泡的显示顺序，气泡可以横向排列展示也可以竖向排列展示(图4d中仅示出横向排列)。进一步来说，当分词数据较多，当前显示界面无法同时呈现所有的分词数据时，还可以左右/上下拖动分词数据，以将排序靠后的分词数据显示，也可以进入到如图4a中示出的详情页面来显示更多的分词数据。
针对步骤S2，在获得至少一个分词数据之后，还可通过S28、检测用户是否切换到其他应用程序，并根据用户切换的应用程序调整分词数据的显示，参见图5a，S28具体包括：
S281、当切换到其他应用程序时，获取所述应用程序的关联信息，所述关联信息包括应用程序的类型或者应用程序中相应输入框的属性信息。
其中，应用程序的类型可以包括以下至少一种：浏览器、邮箱、电话簿、免费电话、购物、在线商店等等。其中，输入框可以是当前光标所在的输入框，输入框的属性信息可以包括文本类输入框、数字类输入框、网址输入框以及混合类输入框等等。
举例来说，当用户切换到Outlook的应用程序时，处理设备110相应检测到当前应用程序的类型为邮箱；当用户将光标放置到浏览器地址栏时，处理设备110相应检测到当前输入框的属性信息为网址输入框。
根据某一实施例，在获得关联信息后，通过S282、根据所述关联信息对分词数据进行过滤，并显示过滤后的分词数据。举例来说，处理设备110对文本信息“比特币最新消息www.****.com”进行切分后，可以获得分词数据“比特币”、“最新”、“消息”、“www.****.com”，然后按照上述确 定分词数据显示优先级的方法来调整各分词数据的显示顺序，比如按照当前热词或者热门话题对分词数据进行热度分析后，确定分词数据的显示顺序依次为“比特币”、“www.****.com”、“最新”、“消息”；当用户切换到Outlook的应用程序时，处理设备110获取到Outlook的类型为邮箱类应用程序，则将“比特币”、“最新”、“消息”过滤，仅显示分词数据“www.****.com”。
根据另一实施例，在获得关联信息后，还可通过S283、根据所述关联信息调整分词数据的显示顺序。具体来说，处理设备110可对分词数据进行分析确定该分词数据与关联信息的匹配程度，并根据匹配程度确定该分词数据的显示优先级，使得匹配程度越高时，分词数据的显示优先级越高，进而将与关联信息越密切的分词数据优先显示给用户，方便用户快速选择需要的分词数据。
比如，将上述示例中的分词数据“www.****.com”的显示优先级调到最高，调整后的分词数据显示顺序为“www.****.com”、“比特币”、“最新”、“消息”。
考虑到用户从复制文本信息到切换应用程序很可能会存在一定的时间间隔，剪贴板中还可以存储用户在不同时间段复制/粘贴的历史文本信息，而间隔的时间越久，用户选择该分词数据的概率就越小，而将间隔时间较久的分词数据显示给用户显然是毫无意义的，还有可能会打扰用户的正常输入和阅读。因此，为了帮助用户快速排除用户不太可能选择的分词数据，将用户最需要的分词数据优先呈现给用户，提高用户获取信息的效率，还可执行如下操作：
参见图5b，当切换到其他应用程序时，通过S2841、计算从复制/剪切文本信息到切换应用程序的间隔时间；然后用过S2842、当所述间隔时间小于预设阈值时，显示分词数据。
具体来说，当用户对应用程序中的某段文本信息执行复制/剪切操作时，处理设备110相应可以获取用户执行该操作的时间戳，记为第一时间，且基于同一文本信息切分得到的分词数据都对应于同一第一时间，基于不同文本信息切分得到的分词数据可以对应不同的第一时间；当用户切换到其他应用程序时，处理设备110可以获取用户执行切换操作的时间戳，记为第二时间，然后处理设备110计算第二时间和每一分词数据对应的第一时间的时间间隔， 并筛选时间间隔小于预设阈值的分词数据，将筛选后的分词数据显示给用户。
比如，当用户切换到浏览器时，仅将5分钟内复制文本信息对应的分词数据“www.****.com”显示给用户，尽管1小时以前用户复制的文本信息中也包含URL地址，但是由于间隔时间较久，用户选择的机率比较小，因此并不会将该1小时以前的URL地址呈现给用户。
进一步来说，对于显示的分词数据，用户还可根据自身需求将两个或者两个以上的分词数据合并为一个分词数据，比如，用户可以依次点选需要合并的分词数据，处理设备110按照点选的顺序对分词数据进行合并，又比如，用户还可以将某一分词数据拖动到另一分词数据的前面、后面，或者该分词数据中的任意两个字符中间，则处理设备110根据被拖动的分词数据停留的位置对两个分词数据进行合并，如此使得对分词数据的编辑更为灵活，方便用户按照自身实际需求获取用户需要的分词数据。
举例来说，对于如图4b显示的分词数据“*”、“变”，“网络解说”、“刘国梁”、“转身”、“这一年”，用户想进一步获取与刘国梁网络解说相关的信息，则用户可以依次点选分词数据“刘国梁”、“网络解说”，或者将分词数据“网络解说”拖动到分词数据“刘国梁”后面，或者将分词数据“刘国梁”拖动到分词数据“网络解说”前面，从而获得合并后的分词数据“刘国梁网络解说”，用户可直接选择该分词数据进而获得与该分词数据关联的推荐信息，也可以将该分词数据发送给其他用户或者粘贴到相应的输入区中。
在显示分词数据之后，接着通过S3、检测用户选择的分词数据。
其中，用户可以通过鼠标、触摸板、触摸屏执行单击、双击、长按、上滑、下滑、左滑或者右滑等操作来选择相应的分词数据；用户也可以通过语音输入设备130来输入语音信息，语音解析设备进行识别、解析后生成相应的语音指令来选择相应的分词数据。
进一步地，处理设备110还可以检测对用户对分词数据执行的具体操作，并根据用户执行的不同操作来对分词数据进行不同的处理。参考图6所示的信息推送方法的流程图，具体包括：
S31、当用户对分词数据执行第一预设操作时，处理设备110显示与该分词数据相关联的推荐信息；S32、当用户对分词数据执行第二预设操作时，处理设备110将该分词数据粘贴到当前输入区。
其中，第一预设操作和第二预设操作可以区别于用户执行合并分词数据 操作的任意操作，比如第一预设操作可以配置为右滑操作，第二预设操作可以配置为单击、双击或者上滑操作等。
这样处理是充分考虑了用户在复制文本信息时可能存在不同的需求，以便为用户提供更为方便、快捷的服务，帮助用户快速输入或者快速获得相关联的推荐信息，尤其是当用户在与其他用户聊天时，用户可以通过信息推送系统方便、快捷地将不同的聊天内容转发给相应的用户，还可以即时了解其他用户讨论的话题，有效地帮助用户更好地参与到聊天中。
举例来说，用户在群聊时接收到了A用户发送的聊天信息“区块链怎么投资”，然后B用户发送了一条聊天信息“你可以参考下这两个www.qkl**1.com,www.qkl**2.com”，用户想进一步了解关于区块链的其他信息，则可对A、B用户发送的聊天信息进行复制，获得分词数据“区块链”、“www.qkl**1.com”、“www.qkl**2.com”、“怎么”、“投资”并呈现给用户，然后用户对分词数据“区块链”执行右滑操作获得与区块链相关联的推荐信息A，又对“www.qkl**1.com”右滑获得相关联的推荐信息B，用户觉得推荐信息B对A用户有帮助，则可以将推荐信息B发送到当前聊天群中，用户还想到自己的朋友C用户对区块链也很感兴趣，则可以将分词数据“www.qkl**1.com”、“www.qkl**2.com”以及推荐信息A、B均发送给C用户。
可以看出，用户在对文本信息进行复制后，仅通过简单的滑动或者点选操作即可满足用户的多重需求，帮助用户方便、快捷地获得相关信息和分享信息，且用户仅需要对文本信息复制一次即可满足用户后续的多维度需求，相比于现有技术中逐个复制关键字检索的方案，本发明的方法可以大大提高用户获取信息以及分享信息的效率。
下面结合相应的附图来进一步解释处理设备110推送推荐信息和粘贴分词数据的方案。
先来看推荐信息的推送，处理设备110通过S4、根据与所述文本信息关联的上下文信息、用户历史聊天记录或者用户画像中的至少一种，对选择的分词数据进行检索，并对检索结果进行过滤，获得与选择的分词数据相关联的推荐信息。
下面结合图7来对步骤S4进一步解释。
首先执行S41、根据与文本信息关联的上下文信息、用户历史聊天记录或者用户画像中的至少一种，匹配相关联的数据库，并基于关联数据库对选 择的分词数据进行检索。
其中，数据库可以是云端数据库，也可以是本地数据库，还可以部分位于云端，部分位于本地。数据库中存储的数据可通过数据爬取装置在各网站、应用程序或者知识库中进行爬取，然后将爬取的数据按照各自分类存储在数据库中。
根据某一实施例，数据库可以按照数据类型进行分类，比如，将数据库分为文字数据库、图片数据库、音频数据库、视频数据库等；
根据另一实施例，数据库还可以按照数据来源对应的类别进行分类，比如，将从亚马逊、淘宝、京东等购物类网站爬取的数据存储到购物类数据库中，将从今日头条、腾讯新闻、微博中爬取的数据存储到资讯类数据库中。进一步还可根据不同的数据来源将各类数据库进一步分类，比如，购物类数据库又包括淘宝数据库、京东数据库以及亚马逊数据库等。
在某些实施例中，也可不对数据库分类，而是根据数据来源对获取的数据进行标识，比如，将从淘宝中爬出的数据都标识为“淘宝”，将从微博中爬取的数据都标识为“微博”，进一步还可根据数据来源所属的类别对于爬取的数据进行标识，比如，将从“淘宝”、“京东”以及“亚马逊”中获取的数据均标识为“购物类”，然后处理设备110根据与文本信息关联的上下文信息、用户历史聊天记录或者用户画像中的至少一种，匹配关联的数据标识，并基于关联的数据标识对检索结果进行过滤，获得与分词数据关联的推荐信息。
在另外一些实施例中，还可通过相应网站或者应用程序提供的数据接口来对选择的分词数据直接进行检索，处理设备110可以根据数据接口对应的应用程序或者网站来对数据接口进行标识或者命名，比如，将淘宝对应的数据接口命名或者标识为“淘宝”；处理设备110还可根据应用程序或者网站所属的类别对数据接口进行标识或者命名，比如，将“淘宝”、“京东”以及“亚马逊”对应的数据接口都标识或者命名为“购物类”，然后处理设备110根据与所述文本信息关联的上下文信息、用户历史聊天记录或者用户画像中的至少一种，匹配关联的网站或者应用程序，并根据关联网站或者关联应用程序提供的数据接口对选择的分词数据进行检索，并对检索结果进行过滤，获得与选择的分词数据相关联的推荐信息。
进一步来说，对于S41，处理设备110可以根据与文本信息关联的上下文信息对选择的分词数据进行语义分析，根据语义分析结果对选择的分词数 据进行检索。
对于同一分词数据，使用不同的数据库对该分词数据进行检索可能会获得不同的结果，比如对于分词数据“篮球”，通过购物类数据库进行检索时获得的是篮球的商品信息，而通过资讯类数据库进行检索时获得的是关于篮球比赛的资讯信息。
因此，为了提供更为符合用户实际需求的检索结果，有必要结合与文本信息关联的上下文信息对选择的分词数据进行语义分析，确定分词数据所属的数据类别，根据数据类别筛选关联的数据内容，进而根据关联数据内容对分词数据进行检索。
其中，处理设备110可通过应用程序提供的数据接口来获取与文本信息关联的上下文信息；也可通过系统提供的数据接口来获取与文本信息关联的上下文信息；处理设备110还可通过检测屏幕画面来获取与文本信息关联的上下文信息，具体来说，处理设备110可在用户对文本信息执行复制/剪切操作时截取屏幕画面，进而通过图文识别技术识别出屏幕画面中的文字信息，并提取出与文本信息关联的上下文信息。
其中，可以采用深度学习算法来进行语义分析，比如通过神经网络对上下文信息进行词性标记、词语切分、实体命名识别以及目的提取，获得用户需求，进而确定分词数据所属的数据类别。
其中，按照待反馈的数据类型可将数据类别划分为文字类、图片类、音频类以及视频类等，针对每一分类，按照数据爬取来源对应的分类还可将数据类别进一步划分为购物子类、资讯子类等，进一步来说，按照数据来源还可对子类别数据进一步划分，比如购物子类又进一步划分为淘宝、京东、亚马逊等。
根据某一实施例，数据类别可以与数据库的分类相对应。处理设备110可以根据分词数据所属的数据类别，匹配与该类别对应的数据库，并基于该数据库对分词数据进行检索。举例来说，对于分词数据“青花瓷”，其关联的上下文信息为“A：推荐一首中国风的歌曲”，“B：青花瓷”，处理设备110通过对上下文信息进行分析可知这里的青花瓷所属的数据类别是音频，则处理设备110可以基于音频数据库对分词数据“青花瓷”进行检索，从而将歌曲“青花瓷.mp3”提供给用户。
在另一实施例中，数据类别也可以与数据标识相对应，处理设备110可以根据分词数据所属的数据类别，确定与该类别相对应的数据标识，并提取 标有该数据标识的数据，然后基于提取的数据对分词数据进行检索。在其他实施例中，数据类别还可以与数据接口的名称/标识相对应，处理设备110可以根据分词数据所属的数据类别，确定与该类别相对应的数据接口名称/标识，并基于该数据接口对分词数据进行检索。
进一步来说，对于S41，处理设备110还可以根据用户历史聊天记录或者用户画像中的至少一种，确定用户习惯、偏好或者兴趣点，并根据用户习惯、偏好或者兴趣点中的至少一种对选择的分词数据进行检索。
其中，对于用户复制/剪切的聊天信息，处理设备110可以通过聊天软件或者系统提供的数据接口来获取用户的历史聊天信息，然后对历史聊天信息进行分析，确定用户习惯、偏好、兴趣点等。
其中，对于用户画像，处理设备110可以根据用户使用终端产生的一系列操作记录来对用户进行分析，构建适于描述用户的一系列标签，并存储到用户画像中，具体来说，可以根据用户浏览的网页、用户下载的数据、用户主动输入或者搜索的信息以及用户设备的GPS信息等确定用户的兴趣和偏好；还可以根据用户使用应用程序的记录确定用户习惯使用的应用程序，进一步还可对应用程序进行分类，确定每一分类中用户习惯使用的应用程序，例如，用户习惯使用的购物类应用程序是京东，用户习惯使用的资讯类应用程序是腾讯新闻，用户习惯使用的浏览器是UC浏览器。
举例来说，用户兴趣点中包括了天气，则当用户选择分词数据“上海”时，处理设备110检索上海的天气信息并反馈给用户；又例如，用户偏好中包括了房产信息，则当用户选择分词数据“上海”时，处理设备110检索上海的房价动态并反馈给用户；再比如，用户经常使用的应用程序是微博，用户的兴趣点中包括了房产，则当用户选择分词数据“上海”时，处理设备110检索微博中关于上海房产的信息并反馈给用户。
进一步地，处理设备110还可先根据与文本信息关联的上下文信息对选择的分词数据进行语义分析，确定分词数据所属的数据类别，并根据用户历史聊天记录或者用户画像中的至少一种，对数据类别中的下级类别进行筛选，基于筛选后的下级数据类别对分词数据进行检索。
比如，对于分词数据“青花瓷”，经语义分析后确定其所属的数据类别为音频类，而通过用户画像获得用户常用酷狗听音乐，则处理设备110可以将酷狗中的歌曲青花瓷反馈给用户。
进一步来说，处理设备110还可根据分词数据的类型来确定分词数据所 属的数据类别，根据数据类别筛选关联的数据内容，进而根据关联数据内容对分词数据进行检索。分词数据的类型例如可以是URL地址、邮箱地址、电话号码等。
举例来说，当获得分词数据为URL地址时，确定分词数据所属的数据类别为浏览器，则根据数据类别筛选分类为浏览器的数据库，或者标识为浏览器的数据接口，通过该数据库或者数据接口检索该URL地址。
更进一步地，处理设备110还可以结合分词数据的类型和用户画像来对分析数据进行检索，比如，获得分词数据为URL地址，且用户画像中记录有用户习惯使用的浏览器为UC浏览器，则直接通过UC浏览器对应的数据库或者数据接口对该URL地址进行检索，获得该URL地址中的内容。
接下来，通过S42、根据用户画像对检索结果进行过滤。
具体来说，处理设备110可以根据用户画像中一个或者多个标签来对检索结果进行过滤。
比如，对于分词数据“篮球”，处理设备110通过腾讯新闻对应的数据库或者数据接口检索到若干条关于篮球赛的检索结果，而根据用户画像可知用户的兴趣点中包括“NBA”和“科比”，则处理设备110可筛选检索结果中与“NBA”和“科比”关联的信息，从而将与用户兴趣点相匹配的检索结果呈献给用户。
接下来，执行S5、显示所述推荐信息。
具体来说，可将推荐信息以卡片形式显示在分词数据附近，用户无需打开相应的应用程序，即可通过阅读卡片内容直接获得推荐信息。
举例来说，对于如图4b示出的分词数据，当用户对分词数据“刘国梁”执行相应操作来获得关于刘国梁的推荐信息时，如图8a所示，推荐信息可以以卡片形式显示在分词数据右侧。用户直接阅读卡片中的信息即可获得推荐的内容。
又比如，对于如图4c示出的分词数据，当用户对分词数据“亲爱的篮球”执行相应操作来获得该分词数据的推荐信息时，如图8b所示，推荐信息可以以卡片形式显示在分词数据右侧。
进一步来说，用户还可以通过执行相应的操作，比如双击或者长按来放大卡片，或者将卡片全屏显示，再次双击或者长按时恢复原卡片大小。另外， 当推荐信息有多条时，用户还可以上下滑动来选择上一条推荐信息或者下一条推荐信息。
进一步来说，对于处理设备110获得的推荐信息，其包含的信息量可能很大，用户需要花费大量的时间来阅读网页原文内容并找到自己需要或者感兴趣的信息，为了进一步提高用户获取信息的效率，处理设备110还可以截取网页中与选择的分词数据相关联的内容，并将截取的内容作为推荐信息呈现给用户。
具体来说，处理设备110可以将分词数据在网页原文中进行检索，获得与分词数据相关联的内容，并截取该部分内容作为推荐信息呈现给用户，从而节省用户阅读时间。当用户需要阅读全文时，可执行相应的操作，比如双击或者长按推荐信息，来获得该推荐信息的网页原文内容。
接下来，执行S6、根据用户对所述推荐信息的操作，将选择的推荐信息粘贴到当前输入区；或者推送并显示与选择的推荐信息相关联的二级推荐信息。
具体来说，当用户对推荐信息执行第三预设操作时，处理设备110将推荐信息粘贴到当前输入区，比如，将推荐信息卡片粘贴到光标所在的输入框中，或者将推荐信息卡片转换为图片格式，再粘贴到当前输入框中，又或者将推荐信息中的文字信息提取出来粘贴到当前输入框。其中，第三预设操作例如可以是点击操作，也可以是其他任意设定操作。
当用户对推荐信息执行第四预设操作时，处理设备110进一步根据推荐信息与其他网页内容的关联性来推荐二级推荐信息，并将二级推荐信息呈现给用户。其中，处理设备110可将与推荐信息具有相似主题、相似分类、相似内容或者具有其他关联性的网页内容作为二级推荐信息。其中，第四预设操作例如可以是右滑操作，也可以是其他任意设定操作。
参见图9所示的信息推送方法流程图，当用户选择分词数据时，还可通过S7、根据用户对分词数据执行的操作，将选择的分词数据粘贴到当前输入区。其中，当前输入区可以是当前页面中光标所在的输入框，也可以用户切换应用程序后，该应用程序的输入框，还可以是编辑文档的输入区，比如word文档；其中，用户执行的操作可以是单击、双击或者上滑操作等。
例如，参见图4a所示的屏幕显示界面，当用户点击分词数据“183****0000”时，分词数据“183****0000”相应粘贴到当前输入框中。
进一步来说，处理设备110可以在当前输入区中已输入内容的后面粘贴选择的分词数据，也可以将选择的分词数据替换当前输入区中的已输入内容。
参见图10所示的信息推送方法流程图，当用户选择分词数据时，还可通过S8、对分词数据的类型进行检测，判断分词数据的类型是否为预设类型；然后通过S9、当分词数据的类型为预设类型时，调用与分词数据的类型相匹配的本地应用程序对分词数据执行预设操作或者显示与分词数据的类型相应的功能选项。
其中，预设类型可以是电话号码、邮箱地址、网址、纯文本或者其他类型等，与电话号码对应的本地应用程序可以是电话簿、免费电话等应用程序，与邮箱地址对应的本地应用程序可以是邮箱类应用程序，与网址对应的本地应用程序可以是浏览器类应用程序，与纯文本对应的本地应用程序可以是用户当前正在使用的应用程序，例如，可通过检测应用程序列表进程获取当前显示在顶层的应用程序，并将该应用程序作为与纯文本对应的本地应用程序。对于其他类型，用户还可以自定义该类型并设定与该类型对应的分词数据，并配置与该类型对应的本地应用程序。
在某一实施例中，本地应用程序可以根据分词数据所属的类型确定预设操作，比如，直接启动相应的本地应用程序并将该电话号码、邮箱地址、网址或者纯文本填充到对应本地应用程序的输入区中，从而大大节省用户输入信息的时间，简化用户操作的复杂度，提高对分词数据的处理效率。
在另一实施例中，本地应用程序还可以根据分词数据所属的类型确定需要显示的功能选项，比如，对于电话号码，当用户选择该电话号码时，可以在该分词数据附近显示与电话号码相关的功能选项，例如可以是“拨打该号码”、“向该号码发送短信”或者“存储该电话号码”等。用户可以根据自身需求选择相应的功能选项，比如“拨打该号码”，本地应用程序相应自动启动并直接执行拨打该电话号码的操作。如此可以大大简化用户操作，方便、快捷地帮助用户快速执行与分词数据相关的功能，提高处理效率。
注意，上述仅为本发明的较佳实施例及所运用技术原理。本领域技术人员会理解，本发明不限于这里所述的特定实施例，对本领域技术人员来说能够进行各种明显的变化、重新调整和替代而不会脱离本发明的保护范围。因此，虽然通过以上实施例对本发明进行了较为详细的说明，但是本发明不仅仅限于以上实施例，在不脱离本发明构思的情况下，还可以包括更多其他等效实施例，而本发明的范围由所附的权利要求范围决定。

Claims (39)

  1. 一种基于剪贴板进行信息推送的方法，其特征在于，包括：
    获取复制/剪切到剪贴板中的文本信息；
    将所述文本信息切分，获得至少一个分词数据，并显示所述分词数据，所述分词数据为文本信息的子集；
    检测用户选择的分词数据；
    根据与所述文本信息关联的上下文信息、用户历史聊天记录或者用户画像中的至少一种，对选择的分词数据进行检索，并对检索结果进行过滤，获得与选择的分词数据相关联的推荐信息；
    显示所述推荐信息。
  2. 根据权利要求1所述的方法，其特征在于，还包括：
    当获得的分词数据在两个以上时，根据用户画像对获得的分词数据进行匹配分析，并调整显示顺序，使得与用户画像匹配度高的分词数据具有更高的显示优先级。
  3. 根据权利要求1所述的方法，其特征在于，还包括：
    当获得的分词数据在两个以上时，根据当前热词或者热门话题对分词数据进行热度分析，并调整显示顺序，使得与当前热词或者热门话题关联的分词数据具有更高的显示优先级。
  4. 根据权利要求1所述的方法，其特征在于，还包括：
    当切换到其他应用程序时，获取所述应用程序的关联信息，所述关联信息包括应用程序的类型或者应用程序中相应输入框的属性信息；
    根据所述关联信息对分词数据进行过滤，并显示过滤后的分词数据；或者
    根据所述关联信息调整分词数据的显示顺序。
  5. 根据权利要求4所述的方法，其特征在于，还包括：
    计算从复制/剪切文本信息到切换应用程序的间隔时间；
    当所述间隔时间小于预设阈值时，显示分词数据。
  6. 根据权利要求1所述的方法，其特征在于，将所述文本信息切分包 括：
    按照相应的分词算法对所述文本信息进行切分。
  7. 根据权利要求1所述的方法，其特征在于，将所述文本信息切分包括：
    根据用户历史粘贴记录或者历史输入记录获取用户切分习惯；
    根据用户切分习惯对所述文本信息进行切分。
  8. 根据权利要求1所述的方法，其特征在于，在获得至少一个分词数据之后，还包括:
    根据用户输入习惯对获得的分词数据进行补充编辑。
  9. 根据权利要求1所述的方法，其特征在于，对选择的分词数据进行检索包括：
    根据与文本信息关联的上下文信息、用户历史聊天记录或者用户画像中的至少一种，匹配相关联的数据库，并基于关联数据库对选择的分词数据进行检索。
  10. 根据权利要求9所述的方法，其特征在于，还包括：
    根据与文本信息关联的上下文信息对选择的分词数据进行语义分析，根据语义分析结果对选择的分词数据进行检索。
  11. 根据权利要求9所述的方法，其特征在于，还包括：
    根据用户历史聊天记录或者用户画像中的至少一种，确定用户习惯、偏好或者兴趣点，并根据用户习惯、偏好或者兴趣点对选择的分词数据进行检索。
  12. 根据权利要求1所述的方法，其特征在于，还包括：
    截取网页中与选择的分词数据相关联的内容，并将截取的内容作为推荐信息。
  13. 根据权利要求1所述的方法，其特征在于，显示所述推荐信息包括：
    将所述推荐信息以卡片形式显示在分词数据附近。
  14. 根据权利要求1所述的方法，其特征在于，还包括：
    根据用户对所述推荐信息的操作，将选择的推荐信息粘贴到当前输入区；或者推送并显示与选择的推荐信息相关联的二级推荐信息。
  15. 根据权利要求1所述的方法，其特征在于，还包括：
    根据用户对选择的分词数据的操作，将选择的分词数据粘贴到当前输入区。
  16. 根据权利要求15所述的方法，其特征在于，将选择的分词数据粘贴到当前输入区包括：
    在当前输入区中已输入内容的后面粘贴选择的分词数据；或者
    将选择的分词数据替换当前输入区中的已输入内容。
  17. 根据权利要求1所述的方法，其特征在于，所述文本信息为用户在聊天场景中复制/剪切的聊天信息。
  18. 根据权利要求1所述的方法，其特征在于，获取复制/剪切到剪贴板中的文本信息包括以下任意一种：
    当检测到用户执行复制/剪切操作时，获取用户复制/剪切的文本信息；或者
    获取最后一次复制/剪切到剪贴板中的文本信息；或者
    获取最近预设次数内复制/剪切到剪贴板中的所有文本信息；或者
    获取预设时间内复制/剪切到剪贴板中的所有文本信息；或者
    获取用户在剪贴板中主动选择的文本信息。
  19. 根据权利要求1所述的方法，其特征在于，还包括：
    根据用户历史操作记录确定用户兴趣点、用户习惯或者用户偏好中的至少一种，并记录到用户画像中。
  20. 根据权利要求1所述的方法，其特征在于，还包括：
    对分词数据的类型进行检测，判断分词数据的类型是否为预设类型；
    当分词数据的类型为预设类型时，调用与分词数据的类型相匹配的本地应用程序对分词数据执行预设操作或者显示与分词数据的类型相应的功能选项。
  21. 一种基于剪贴板的信息推送系统，其特征在于，包括处理设备、存储设备、输入设备以及显示设备；
    所述输入设备，适于检测用户执行的输入操作；其中，所述输入操作至少包括复制/剪切操作，以及对分词数据的选择；
    所述处理设备，适于执行切分操作以及推送操作；
    其中，所述切分操作至少包括：
    根据所述输入设备获取的复制/剪切操作，获取复制/剪切的文本信息；
    将所述文本信息切分，获得至少一个分词数据；
    将所述分词数据发送至显示设备；
    其中，所述分词数据为所述文本信息的子集；
    以及所述推送操作至少包括：
    根据所述输入设备获取的用户操作，获取所选择的分词数据；
    根据与所述文本信息关联的上下文信息、用户历史聊天记录或者用户画像中的至少一种，对所选择的分词数据进行检索，并对检索结果进行过滤，获得与所述选择的分词数据相关联的推荐信息；
    将所述推荐信息发送至所述显示设备；
    所述存储设备，包括剪贴板以及包含推荐信息的数据库；其中，所述剪贴板适于保存所述复制/剪贴的文本信息；
    所述显示设备，适于显示文本信息，并根据处理设备的操作显示对应的分词数据和/或推荐信息。
  22. 根据权利要求21所述的系统，其特征在于，还包括：
    当获得的分词数据在两个以上时，处理设备根据用户画像对获得的分词数据进行匹配分析，并调整显示顺序，使得与用户画像匹配度高的分词数据具有更高的显示优先级。
  23. 根据权利要求21所述的系统，其特征在于，还包括：
    当获得的分词数据在两个以上时，处理设备根据当前热词或者热门话题 对分词数据进行热度分析，并调整显示顺序，使得与当前热词或者热门话题关联的分词数据具有更高的显示优先级。
  24. 根据权利要求21所述的系统，其特征在于，还包括：
    当切换到其他应用程序时，处理设备获取所述应用程序的关联信息，所述关联信息包括应用程序的类型或者应用程序中相应输入框的属性信息；
    处理设备根据所述关联信息对分词数据进行过滤，并显示过滤后的分词数据；或者
    根据所述关联信息调整分词数据的显示顺序。
  25. 根据权利要求24所述的系统，其特征在于，还包括：
    处理设备计算从复制/剪切文本信息到切换应用程序的间隔时间；
    当所述间隔时间小于预设阈值时，通过显示设备显示分词数据。
  26. 根据权利要求21所述的系统，其特征在于，将所述文本信息切分包括：
    按照相应的分词算法对所述文本信息进行切分；或者
    根据用户历史粘贴记录或者历史输入记录获取用户切分习惯，根据用户切分习惯对所述文本信息进行切分。
  27. 根据权利要求21所述的系统，其特征在于，在获得至少一个分词数据之后，还包括:
    处理设备根据用户输入习惯对获得的分词数据进行补充编辑。
  28. 根据权利要求21所述的系统，其特征在于，对选择的分词数据进行检索包括：
    处理设备根据与文本信息关联的上下文信息、用户历史聊天记录或者用户画像中的至少一种，匹配相关联的数据库，并基于关联数据库对选择的分词数据进行检索。
  29. 根据权利要求28所述的系统，其特征在于，还包括：
    处理设备根据与文本信息关联的上下文信息对选择的分词数据进行语义分析，根据语义分析结果对选择的分词数据进行检索。
  30. 根据权利要求28所述的系统，其特征在于，还包括：
    处理设备根据用户历史聊天记录或者用户画像中的至少一种，确定用户习惯、偏好或者兴趣点，并根据用户习惯、偏好或者兴趣点对选择的分词数据进行检索。
  31. 根据权利要求21所述的系统，其特征在于，还包括：
    处理设备截取网页中与选择的分词数据相关联的内容，并将截取的内容作为推荐信息。
  32. 根据权利要求21所述的系统，其特征在于，显示所述推荐信息包括：
    通过显示设备将所述推荐信息以卡片形式显示在分词数据附近。
  33. 根据权利要求21所述的系统，其特征在于，还包括：
    处理设备根据用户对所述推荐信息的操作，将选择的推荐信息粘贴到当前输入区；或者推送并显示与选择的推荐信息相关联的二级推荐信息。
  34. 根据权利要求21所述的系统，其特征在于，还包括：
    处理设备根据用户对选择的分词数据的操作，将选择的分词数据粘贴到当前输入区。
  35. 根据权利要求34所述的系统，其特征在于，将选择的分词数据粘贴到当前输入区包括：
    在当前输入区中已输入内容的后面粘贴选择的分词数据；或者
    将选择的分词数据替换当前输入区中的已输入内容。
  36. 根据权利要求21所述的系统，其特征在于，所述文本信息为用户在聊天场景中复制/剪切的聊天信息。
  37. 根据权利要求21所述的系统，其特征在于，获取复制/剪切到剪贴板中的文本信息包括以下任意一种：
    当检测到用户执行复制/剪切操作时，获取用户复制/剪切的文本信息；或者
    获取最后一次复制/剪切到剪贴板中的文本信息；或者
    获取最近预设次数内复制/剪切到剪贴板中的所有文本信息；或者
    获取预设时间内复制/剪切到剪贴板中的所有文本信息；或者
    获取用户在剪贴板中主动选择的文本信息。
  38. 根据权利要求21所述的系统，其特征在于，还包括：
    处理设备对分词数据的类型进行检测，判断分词数据的类型是否为预设类型，当分词数据的类型为预设类型时，调用与分词数据的类型相匹配的本地应用程序对分词数据执行预设操作或者显示与分词数据的类型相应的功能选项。
  39. 一种终端设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，其特征在于，所述处理器执行的程序包括如权利要求1-20任一项所述的方法。
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