JP2015064759A - Electronic device, conversion candidate registration program, and conversion candidate registration method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve efficiency of a conversion candidate registration in a character string containing a delimiter.SOLUTION: An electric device 10 includes a memory 13 and a processor 11. The memory 13 stores a conversion candidate which is a conversion character candidate for an input character. The processor 11 associates a plurality of words divided by a predetermined delimiter with a series of words having a correlation to each other, and registers the associated series of words and the delimiter which divides the series of words integrally in the conversion candidate.

Description

  The present invention relates to an electronic device, a conversion candidate registration program, and a conversion candidate registration method.

  For electronic devices that can input characters, such as computers, smartphones, tablet terminals, car navigation devices, etc., to convert the input character string of kana characters into a character string that includes Chinese characters in order to facilitate the input of Chinese characters The conversion dictionary is provided. In “Kana-Kanji conversion” using a conversion dictionary, past conversion results are registered in the conversion dictionary as needed as conversion candidates for an input character string.

JP 2000-172686 A

  When the input character string includes a plurality of words and a “separator” that separates the plurality of words, it is determined whether or not the plurality of words separated by the delimiter have meaning as a whole. Difficult to do. Therefore, when a delimiter is included in the input character string, the conversion result of each word delimited by the delimiter is registered in the conversion dictionary as a conversion candidate instead of the conversion result of the entire character string. There are many cases. For example, if the conversion result includes a space and a punctuation mark, such as “Japan Corporation A-like, B-like”, “Japan Corporation”, “A-like”, “B-like” Are often registered in the conversion dictionary.

  Therefore, even if a character string including a plurality of words and a delimiter is a character string that is frequently input by the user, when the user converts the character string to Kana-Kanji, conversion is required for each individual word. Become. For this reason, a user's effort increases and the efficiency of Kanji input falls.

  On the other hand, in order to prevent a decrease in the efficiency of inputting Chinese characters, the user can manually register in advance in the conversion dictionary a character string including a plurality of words and delimiters. However, manual registration increases user effort and is inefficient.

  The disclosed technology has been made in view of the above, and provides an electronic device, a conversion candidate registration program, and a conversion candidate registration method that can increase the efficiency of registration of conversion candidates for a character string including a delimiter. With the goal.

  In the disclosed aspect, conversion candidates that are conversion character candidates for the input character are stored. In addition, a series of words correlated with each other in a plurality of words delimited by a predetermined delimiter are associated. In addition, a series of related words and a delimiter that separates the series of words are registered together as a conversion candidate.

  According to the disclosed aspect, the efficiency of registering conversion candidates for a character string including a delimiter can be increased.

FIG. 1 is a diagram illustrating a hardware configuration example of the electronic apparatus according to the first embodiment. FIG. 2 is a diagram illustrating an example of address book registration according to the first embodiment. FIG. 3 is a diagram illustrating an example of a group list according to the first embodiment. FIG. 4A is a diagram for explaining the operation of the electronic apparatus according to the first embodiment. FIG. 4B is a diagram for explaining the operation of the electronic apparatus according to the first embodiment. FIG. 4C is a diagram for explaining the operation of the electronic apparatus according to the first embodiment. FIG. 4D is a diagram for explaining the operation of the electronic apparatus according to the first embodiment. FIG. 5A is a diagram for explaining the operation of the electronic apparatus according to the first embodiment. FIG. 5B is a diagram for explaining the operation of the electronic apparatus according to the first embodiment. FIG. 5C is a diagram for explaining the operation of the electronic apparatus according to the first embodiment. FIG. 5D is a diagram for explaining the operation of the electronic apparatus according to the first embodiment. FIG. 6 is a flowchart for explaining processing of the electronic apparatus according to the first embodiment.

  Embodiments of an electronic device, a conversion candidate registration program, and a conversion candidate registration method disclosed in the present application will be described below in detail with reference to the drawings. In addition, the electronic device, the conversion candidate registration program, and the conversion candidate registration method disclosed in the present application are not limited by this embodiment. Further, in the following embodiments, configurations having the same function and steps for performing the same processing are denoted by the same reference numerals, and redundant description is omitted.

[Example 1]
<Hardware configuration of electronic equipment>
FIG. 1 is a diagram illustrating a hardware configuration example of the electronic apparatus according to the first embodiment. In FIG. 1, the electronic device 10 includes a processor 11, a touch panel 12, and a memory 13. Examples of the electronic device 10 include a computer capable of inputting characters, a smartphone, a tablet terminal, a car navigation device, and the like.

  The processor 11 performs various processes of the electronic device 10. In particular, the processor 11 registers conversion character candidates (that is, “conversion candidates”) for characters (that is, “input characters”) input to the electronic device 10 in the conversion dictionary 131 stored in the memory 13. Examples of the processor 11 include a central processing unit (CPU), a digital signal processor (DSP), and a field programmable gate array (FPGA).

  The touch panel 12 is attached to the surface of the electronic device 10, accepts input operations including character input, and displays various types of information.

  The memory 13 stores a conversion dictionary 131 in which conversion candidates are registered, and an address book 132 in which a plurality of entries are registered. The memory 13 stores various programs. Examples of the memory 13 include a random access memory (RAM) such as an SDRAM (Synchronous Dynamic Random Access Memory), a read only memory (ROM), a flash memory, and the like.

<Operation of electronic equipment>
FIG. 2 is a diagram illustrating an example of address book registration according to the first embodiment. FIG. 3 is a diagram illustrating an example of a group list according to the first embodiment.

  For example, as shown in FIG. 2, entries 21, 22, and 23 are registered in advance in the address book 132 by the user. In the entries 21, 22, and 23, “first information” that can uniquely identify each entry is registered in the upper item, and “second information” indicating the group to which the entry belongs is registered in the lower item. Is registered. Here, “contact names” such as “like A”, “like B”, and “like C” are registered as “first information”, and these contact names search for entries. It becomes the primary key when In addition, as “second information”, “affiliated company name” representing a group to which each contact address belongs, such as “Company F” and “Company D”, for example, is registered.

  Further, as shown in FIG. 3, the group list 30 is registered in advance in the address book 132 by the user. The group name 31 is “F company” and the contact names 32-1 and 32-2 belonging to “F company” are registered in accordance with the fact that the affiliated company name registered in the entries 21 and 22 is “F company”. A group list 30 for “A-like” and “B-like” is registered. That is, the contact names “A-like” and “B-like” are registered in the same group. In the group list 30, the contact names 32-1 and 32-2 correspond to the above “first information”, and the group name 31 corresponds to the above “second information” indicating the group to which the entry belongs. . The group name 31 serves as a primary key when searching the group list 30.

  Using the address book 132 in which such entries and group lists are registered, the processor 11 registers conversion candidates in the conversion dictionary 131 as follows. In the following, two registration examples, Registration Example 1 and Registration Example 2, are given. 4A to 4D and 5A to 5D are diagrams for explaining the operation of the electronic apparatus of the first embodiment.

<Registration example 1>
Registration example 1 will be described with reference to FIGS.

  The conversion result “A-like, B-like (Company F), C-like (Company D)” of the kana character string input using the touch panel 12 is displayed on the touch panel 12 and confirmed. A key or a line feed key is touched to determine the conversion result (FIG. 4A). The conversion result shown in FIG. 4A is obtained by dividing a plurality of words “A-like”, “B-like”, “Company F”, “C-like”, “Company D”, and “,”, “ And a predetermined delimiter (“,”).

  When the conversion result is confirmed, the processor 11 removes a predetermined delimiter from the conversion results “A-like, B-like (Company F), C-like (Company D)”, a plurality of words “A-like”, “B-like”, “Company F”, “C-like” and “Company D” are extracted (FIG. 4B). The predetermined delimiters “,”, “(”, “)” are registered in the memory 13 in advance.

  Next, the processor 11 selects “word 1” which is two words adjacent to each other in the extracted words “like A”, “like B”, “company F”, “like C”, and “company D”. The presence or absence of correlation with “word 2” is determined with reference to the address book 132 (FIG. 4C).

  When the word 1 is “like A” and the word 2 is “like B”, in the group list 30, the word 1 matches the contact name 32-1, and the word 2 matches the contact name 32-2. To do. That is, in the group list 30, “Like A” and “Like B” are registered in the same group “Company F”. Therefore, the processor 11 determines and associates “A-like” and “B-like” with a series of words that are correlated with each other.

  When the word 1 is “B” and the word 2 is “Company F”, the word 1 matches the contact name of the entry 22, and the word 2 matches the company name of the entry 22. That is, “B” and “Company F” are registered in the same entry 22. Therefore, the processor 11 determines and associates “Like B” and “Company F” with a series of words that are correlated with each other.

  As a result of associating “Like A” and “Like B” and associating “Like B” with “Company F”, “Like A”, “Like B”, and “Company F” are correlated with each other. Associated as a series of words.

  When the word 1 is “Company F” and the word 2 is “C-like”, as shown in FIG. 2, “F Company” and “C-like” are not registered in the same entry. Further, as shown in FIG. 3, “C-like” is not registered in the group list 30 of “Company F”. Therefore, the processor 11 determines that there is no correlation between “Company F” and “C-like”, and does not associate “F Company” with “C-like”.

  When the word 1 is “C” and the word 2 is “Company D”, the word 1 matches the contact name of the entry 23, and the word 2 matches the company name of the entry 23. That is, “C-like” and “Company D” are registered in the same entry 23. Therefore, the processor 11 determines and associates “C-like” and “Company D” with a series of words that are correlated with each other.

  Next, the processor 11 registers a series of related words and a delimiter that separates the series of words as conversion candidates in the conversion dictionary 131 (FIG. 4D).

  That is, the processor 11 associates “A-like”, “B-like”, “F” associated as a series of words from the conversion results “A-like, B-like (Company F), C-like (Company D)” shown in FIG. 4A. "Company" and separators ",", "(", ")" are extracted as a unit. At this time, the processor 11 performs extraction by setting the delimiter at the end point of extraction as “)”. In other words, the processor 11 extracts “A-like, B-like (Company F)” from “A-like, B-like (Company F), C-like (Company D)”. Then, the processor 11 registers the extracted “A-like, B-like (Company F)” as a conversion candidate for the reading “Esama”. This reading “E-sama” is “A-like, B-like” among the kana characters entered when obtaining the conversion results “A-like, B-like (Company F), C-like (Company D)” shown in FIG. 4A. Kana characters corresponding to the first word “Ms. A” in (Company F) ”are extracted. Therefore, when a character string of the kana character “E-sama” is input to the touch panel 12 after registration of the conversion candidate, “A-like, B-like (Company F)” including a delimiter as the conversion candidate for the character string. "Is displayed on the touch panel 12.

  Further, the processor 11 separates the conversion results “A-like, B-like (Company F), C-like (Company D)” shown in FIG. 4A into a series of words “C-like” and “D-Company”. The symbols “(”, “)” are extracted as a unit. That is, the processor 11 extracts “C-like (Company D)” from “A-like, B-like (Company F), C-like (Company D)”. Then, the processor 11 reads the extracted “C-like (Company D)” and registers it as a conversion candidate for “Shisa-sama”. This reading “Shi-sama” is “C-like” (D-like) among the kana characters entered when obtaining the conversion result “A-like, B-like (Company F), C-like (Company D)” shown in FIG. 4A. The kana characters corresponding to the first word “C-like” are extracted. Therefore, when a character string of the kana character “Shisa-sama” is input to the touch panel 12 after registration of the conversion candidate, “C-like (Company D)” including a delimiter is used as the conversion candidate for the character string. It is displayed on the touch panel 12.

<Registration example 2>
Registration example 2 will be described with reference to FIGS.

  The conversion result of the character string of the kana character input using the touch panel 12 "F company: A-like, B-like D company: C-like" is displayed on the touch panel 12, and the confirmation key or line feed on the touch panel 12 The key is touched to confirm the conversion result (FIG. 5A). The conversion result shown in FIG. 5A is obtained by dividing the plurality of words “Company F”, “Like A”, “Like B”, “Company D”, “Like C”, and “:”, “ And a predetermined delimiter of “space”.

  When the conversion result is finalized, the processor 11 removes a predetermined delimiter from the conversion result “Company F: A, B, D: C”, and a plurality of words “Company F”, “A” ”,“ B-like ”,“ D company ”, and“ C-like ”are extracted (FIG. 5B). The predetermined delimiters “:” and “space” are registered in the memory 13 in advance.

  Next, the processor 11 selects “word 1” which is two words adjacent to each other in the extracted plural words “F company”, “A like”, “B like”, “D company”, “C like”. The presence or absence of correlation with “word 2” is determined with reference to the address book 132 (FIG. 5C).

  When the word 1 is “Company F” and the word 2 is “Like A”, the word 1 matches the company name of the entry 21 and the word 2 matches the contact name of the entry 21. That is, “Company F” and “Like A” are registered in the same entry 21. Therefore, the processor 11 determines and associates “Company F” and “Like A” with a series of words that are correlated with each other.

  When the word 1 is “like A” and the word 2 is “like B”, in the group list 30, the word 1 matches the contact name 32-1, and the word 2 matches the contact name 32-2. To do. That is, in the group list 30, “Like A” and “Like B” are registered in the same group “Company F”. Therefore, the processor 11 determines and associates “A-like” and “B-like” with a series of words that are correlated with each other.

  Then, “Company F” is associated with “A-like”, and “A-like” is associated with “B-like”. As a result, “Company F”, “A-like”, and “B-like” are correlated with each other. Associated as a series of words.

  When the word 1 is “B” and the word 2 is “D”, as shown in FIG. 2, “B” and “D” are not registered in the same entry. Also, as shown in FIG. 3, there is no group list for “Company D”. Therefore, the processor 11 determines that there is no correlation between “Like B” and “Company D”, and does not associate “Like B” with “D Company”.

  When the word 1 is “Company D” and the word 2 is “C-like”, the word 1 matches the company name of the entry 23 and the word 2 matches the contact name of the entry 23. That is, “Company D” and “Ms. C” are registered in the same entry 23. Therefore, the processor 11 determines and associates “Company D” and “C-like” with a series of words that are correlated with each other.

  Next, the processor 11 registers a series of related words and a delimiter that separates the series of words as conversion candidates in the conversion dictionary 131 (FIG. 5D).

  That is, the processor 11 uses the conversion results “Company F: A-like, B-like D-company: C-like” shown in FIG. The separators “:”, “,” are extracted as a unit. That is, the processor 11 extracts “F company: A-like, B-like” from “F company: A-like, B-like D company: C-like”. Then, the processor 11 registers the extracted “Company F: A-like, B-like” as a conversion candidate for the reading “Efusha”. This reading “Efusha” is “F Company: A-like, B” among the kana characters entered when obtaining the conversion result “Company F: A-like, B-like D-company: C-like” shown in FIG. 5A. The kana character corresponding to the first word “Company F” in “Sama” is extracted. Therefore, when a character string of a kana character “Efusha” is input to the touch panel 12 after registration of the conversion candidate, “F company: A-like, B-like including a delimiter as a conversion candidate of the character string” "Is displayed on the touch panel 12.

  5A from the conversion result “Company F: A-like, B-like D-Company: C-like” shown in FIG. 5A, and the delimiter “: ] As a unit. That is, the processor 11 extracts “D company: C-like” from “F company: A-like, B-like D company: C-like”. Then, the processor 11 reads the extracted “Company D: Mr. C” and registers it as a conversion candidate for “Diisha”. This reading “Diisha” is “D company: C” among the kana characters entered when obtaining the conversion result “Company F: A-like, B-like D-company: C-like” shown in FIG. 5A. The kana characters corresponding to the first word “Company D” are extracted. Therefore, when the character string of the kana character “Disha” is input to the touch panel 12 after registration of the conversion candidate, “D company: C” including a delimiter is included as the conversion candidate of the character string. It is displayed on the touch panel 12.

<Processing electronic devices>
FIG. 6 is a flowchart for explaining processing of the electronic apparatus according to the first embodiment. The flowchart shown in FIG. 6 starts when the conversion result of the kana character string is displayed on the touch panel 12 and the conversion result is fixed by touching the confirmation key or the line feed key on the touch panel 12. Is done.

  First, the processor 11 extracts a plurality of words excluding a predetermined delimiter from the conversion result character string (step S61).

  Next, the processor 11 searches the address book 132 using each of the two words “word 1” and “word 2” that are adjacent to each other among the plurality of extracted words (step S62).

  Next, the processor 11 determines whether or not the word 1 and the word 2 are registered in the same entry of the address book 132 (step S63).

  When the word 1 and the word 2 are registered in the same entry (step S63: Yes), the processor 11 determines that the word 1 and the word 2 are “correlated”, and the word 1 and the word 2 are A series of words that are correlated with each other are determined and associated (step S64).

  When word 1 and word 2 are not registered in the same entry (step S63: No), processor 11 determines whether word 1 and word 2 are registered in the same group of address book 132 or not. (Step S65).

  If the word 1 and the word 2 are registered in the same group (step S65: Yes), the processor 11 determines that the word 1 and the word 2 are “correlated”, and the word 1 and the word 2 are A series of words that are correlated with each other are determined and associated (step S64).

  When the word 1 and the word 2 are not registered in the same entry (step S63: No) and are not registered in the same group (step S65: No), the processor 11 The word 2 is determined to be “no correlation”, and the word 1 and the word 2 are not associated (step S66).

  Next, the processor 11 determines whether or not all words extracted in step S61 have been correlated (step S67).

  When there is a word for which the presence / absence of correlation is not determined (step S67: No), the processor 11 shifts the determination target word among the plurality of words extracted in step S61 (step S68). For example, the processor 11 shifts the word 1 and the word 2 to be determined backward by one word. Then, the process returns to step S62.

  When the determination of the presence / absence of correlation of all the words extracted in step S61 is completed (step S67: Yes), the processor 11 determines whether or not there are words correlated with each other in the plurality of words extracted in step S61. (Step S69).

  If there is a word having a correlation (step S69: Yes), the processor 11 registers the associated series of words and the delimiters that delimit these series of words together as a conversion candidate in the conversion dictionary 131 ( Step S70), the process is terminated.

  If there is no correlated word (step S69: No), the processor 11 ends the process without registering the conversion candidate.

  As described above, according to this embodiment, the electronic device 10 includes the memory 13 and the processor 11. The memory 13 stores conversion candidates that are conversion character candidates for the input character. The processor 11 associates a series of words correlated with each other in a plurality of words separated by a predetermined delimiter. Then, the processor 11 registers a series of related words and a delimiter that separates the series of words as a unit into the conversion candidate.

  By doing this, it is possible to automatically register a series of words that have meaning as one of a plurality of words separated by a delimiter as conversion candidates with the delimiter included. The efficiency of registering conversion candidates for a column can be increased. In addition, since a series of meaningful words separated by a delimiter can be presented as conversion candidates for a character string that does not include a delimiter, it is possible to reduce the trouble of character string conversion.

  Further, the processor 11 determines the presence / absence of correlation in a plurality of words using a contact name that can uniquely identify an entry in the address book 132 and a company name indicating a group to which the entry belongs.

  In this way, a series of words having meaning as a whole in a plurality of words separated by a delimiter can be determined using an existing database called the address book 132, so a series of words having meaning as a whole. Can be easily determined.

  Further, the processor 11 selects the word 1 and the word 2 when the word 1 matching the contact name and the word 2 matching the company name are registered in the same entry among the plurality of words. It is determined as a series of words that are correlated with each other.

  By doing so, for example, the name of the person and the name of the company to which the person belongs can be registered in the conversion candidate as a series of meaningful words as a whole.

  Further, the processor 11 correlates the word 1 and the word 2 with each other when the word 1 and the word 2 that respectively match different contact names among the plurality of words are registered in the same group. Judged as a series of words.

  In this way, for example, the names of a plurality of persons belonging to the same group can be registered as conversion candidates as a series of meaningful words.

[Other embodiments]
[1] Each process in the above description in the electronic device 10 may be realized by causing the processor 11 to execute a program corresponding to each process. For example, a program corresponding to each process in the above description may be stored in the memory 13, and each program may be read from the memory 13 and executed by the processor 11. Each program is not necessarily stored in the memory 13 in advance. That is, for example, each program is recorded in advance on a portable recording medium such as a magnetic disk, an optical disk, an IC card, or a memory card that can be connected to the electronic device 10, and each program is read from the recording medium and executed by the processor 11. May be. Further, for example, each program may be stored in advance in a computer or server connected to the electronic device 10 wirelessly or by wire via the Internet, LAN, WAN, etc., and each program may be read out and executed by the processor 11. .

  [2] In the above description, a punctuation mark, parentheses, colon, and space are given as examples of the predetermined delimiter. However, the predetermined delimiters are not limited to punctuation marks, parentheses, colons, and spaces. For example, as a predetermined delimiter, a punctuation mark, a comma, a semicolon, or the like can be set. The user can register an arbitrary delimiter in the memory 13 in advance.

  [3] In the above description, both the processing of step S63 and the processing of step S65 are performed as the determination processing of the presence / absence of correlation. However, the correlation presence / absence determination process may be performed by either one of the process in step S63 and the process in step S65.

  [4] In the above description, “contact name” is given as an example of “first information” that can uniquely identify each entry, and “company name” is given as an example of “second information” representing a group. Listed. However, the first information and the second information are not limited to the contact name and the affiliated company name, and can be arbitrarily set by the user.

  [5] The address book 132 is not necessarily stored in the memory 13. That is, for example, the processor 11 may refer to the address book 132 stored in a computer or a server connected to the electronic device 10 wirelessly or by wire via the Internet, LAN, WAN, or the like.

  [6] In the above description, the address book 132 is given as an example of an existing database used for determining the presence or absence of correlation. However, the existing database used for determining the presence or absence of correlation is not limited to the address book 132. For example, the presence or absence of correlation may be determined using a schedule book or the like that is an existing database.

DESCRIPTION OF SYMBOLS 10 Electronic device 11 Processor 12 Touch panel 13 Memory 131 Conversion dictionary 132 Address book

Claims (6)

A memory for storing conversion candidates that are conversion character candidates for the input character;
A processor that associates a series of words correlated with each other in a plurality of words delimited by a predetermined delimiter, and registers the associated series of words and the delimiter that delimits the series of words together in the conversion candidate; ,
An electronic device comprising: The processor determines the presence or absence of the correlation in the plurality of words using first information that can uniquely identify an address book entry and second information indicating a group to which the entry belongs.
The electronic device according to claim 1. The processor, when the first word that matches the first information and the second word that matches the second information are registered in the same entry among the plurality of words, Determining the first word and the second word as the series of words correlated to each other;
The electronic device according to claim 2. The processor, when a first word and a second word that respectively match a plurality of different first information among the plurality of words are registered in the same group, the first And the second word are determined as the series of words correlated with each other,
The electronic device according to claim 2. In a processor provided in an electronic device that stores conversion candidates that are conversion character candidates for input characters,
Associating a set of words that are correlated with each other in words separated by a given delimiter,
A conversion candidate registration program that executes a process of registering the series of related words and the delimiter that separates the series of words as a unit in the conversion candidate. A word registration method in an electronic device that stores conversion candidates that are conversion character candidates for an input character,
Associating a set of words that are correlated with each other in words separated by a given delimiter,
Registering the series of associated words and the delimiter that separates the series of words together in the conversion candidate;
Conversion candidate registration method.

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