JP2002351867A - Document processor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve usability of an idiom retrieval display function and facilitate the production of document by combining an idiom retrieval display function and an example display function optimally on a document processor such like a Japanese word processor provided with a function to retrieve and display an idiom relating to a word. SOLUTION: The document processor informed a user of existence of related idiom by adding a star mark, for homonym which has related idioms among plural homonyms of KANA (Japanese syllabary)/KANJI (Chinese character) converting object.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a document processing apparatus. In particular, it relates to a Japanese word processor (word processor) having a function of searching for and displaying idioms related to words. The present application also relates to a word processor having a function of displaying an example (sentence).

[0002]

2. Description of the Related Art As a function for assisting document creation in a word processor, there are an example sentence display function and a phrase search display function as disclosed in Japanese Patent Application Laid-Open No. 3-257574 (G06F15 / 20).
This well-known example sentence display function will be briefly described.
When performing kana-kanji conversion in a word processor, the user needs to select homonyms. However, in some homonyms,
There are some things that are confusing to use properly.

In such a case, it is necessary to check which word should be used. For this reason, if you press the example dictionary key after entering the kana in Roman alphabet input, etc., a plurality of example sentences containing homonyms corresponding to this kana input will be displayed, and the user will select the one that seems appropriate from this , Select and specify. Japanese Patent Application Laid-Open No. Sho 62-175860 (G06F15 / 2) discloses an example sentence of a plurality of homonyms.
0).

[0004] Conventionally, when there is a word to be referred to in the displayed example sentence, the user has to remember the word and operate the example display again with the remembered word. . The well-known phrase search and display function will be briefly described. In a word processor, as one of functions for assisting a user in creating a sentence, there is a function of inputting a word and searching for and displaying idioms related to the word.

[0005] That is, even when the user wants to use idioms such as four-character idioms in a document, the user cannot clearly use the four-character idioms unless they know the meaning and notation clearly. Therefore, it is conceivable to search and display idioms by using words associated with the idioms as keywords. As such a technique, there is JP-A-4-77951 (G06F15 / 20). In the technique of this publication, not only words but also their simple meanings are input and searched.

[0006] In this way, even idioms of slang can be easily searched. By the way, the idiom search display function is originally provided for a user who does not know much idioms. That is, the user who does not know the idiom is less likely to use the idiom search and display function.

[0007] Further, even if the idiom search and display function searches for an idiom with respect to an input word, if the idiom related to this word is "present or not?", The instruction key of the idiom search and display function is pressed. Until then, it becomes trial and error, and the operability deteriorates.

Incidentally, although the timing is different from the present application,
Japanese Patent Publication No. 154152 (G06F15 / 20) discloses that the presence of a related example is identified and displayed.

[0009]

SUMMARY OF THE INVENTION An object of the present invention is to improve the degree of use of the idiom retrieval and display function.

[0010] Further, it is confusing to display a four-character idiom for a certain word and an example sentence in a mixed manner to assist the user in creating a document. Thus, the idiom search display function and the example display function are optimally combined to assist the user in document creation.

[0011]

[Means for Solving the Problems]

The document processing apparatus according to the present invention comprises a related phrase search means (17) for detecting whether or not there is a phrase related to a plurality of homonyms in the kana input of the kana-kanji conversion object; When displayed, identification display means (10) for displaying together with the search result (308) of the related idiom search means (17) to identify and display the presence or absence of idioms related to the homophonic meaning words. And

[0013]

According to the present invention, when displaying plural homonyms,
If there is a phrase associated with the homonym word, the user is notified of this.

[0014]

DESCRIPTION OF THE PREFERRED EMBODIMENTS For the sake of simplicity, the first embodiment will be described first focusing on the contents displayed on the screen, and then the second embodiment will be described focusing on the internal operation.

(A) Description of the first embodiment. A first embodiment of the present invention will be described with reference to FIGS. 1 to 10 and FIG. FIG. 1 shows the appearance of the Japanese word processor (word processor). In FIG. 1, (1) is an input unit,
Consists of a keyboard. (1a) is a kana-kanji conversion key.
(1b) is an example dictionary key. (1c) is a four-character idiom search key. (1d) is a next word search instruction key. (5) is an output unit, which comprises a liquid crystal display screen.

FIG. 2 is a diagram showing an operation of displaying an example of the word processor. The operation of the first embodiment will be described with reference to FIGS.
This will be described below with reference to FIGS. 3 to 10 and FIG. 36 showing the contents of the display screen.

First, by operating the keyboard (1), as shown in FIG. 3, readings are displayed by kana input or Roman character input. In the case of FIG. 3, "I meet Koibito" was input.
In FIG. 3, (K) is a cursor display, and (L) is an underline indicating that the character is to be converted.

Here, when the Kana-Kanji conversion key (1a) of the keyboard (1) is pressed, as shown in FIG. 4, the Kana-Kanji conversion is performed and "Meet a lover" is displayed.

Next, when the example dictionary key (1b) is pressed, the operation is performed according to FIG. That is, here, the kana-kanji conversion has already been performed. Since "meet a lover" is composed of a phrase "meet a lover" and a phrase "meet", information of the word "meet" corresponding to the last phrase "meet" is extracted. This information means that the word itself "meets" and the part of speech of this word "verb"
"Read".

Then, a plurality of homonyms are searched internally. Further, a four-character idiom associated with the plurality of homonyms is also searched to determine whether or not the four-character idiom exists.

Next, a plurality of homonyms and their examples are displayed. At this time, if there is a four-character idiom for the homonym, this homonym is displayed with “★” or “★”. If there is no four-character idiom, it is displayed with “[”, “]”. To display. That is, they are displayed as shown in FIG. In FIG. 5, (5a) is an example display area. In the example display area (5a), three homonyms of the reading "Au" are displayed, and up to three examples are displayed for each. As can be seen from FIG. 5, "meet" has a related four-character idiom.

Here, when the user wants to display a four-character idiom associated with the "meet", the cursor is moved to the "meet".
Move up and press the four-character idiom search key (1c). As a result, the four-character idiom and the meaning are displayed in the four-character idiom display area (5b) as shown in FIG.

In the above description of the operation, "meet the child"
After pressing, the Kana-Kanji conversion key (1a) was pressed to convert to "meet a lover," and then the example dictionary key (1b) was pressed. However, as can be seen from the operation description in FIG. 2, even if the kana-kanji conversion key (1a) is not pressed, if the example dictionary key (1b) is pressed, the kana-kanji conversion operation is automatically performed and displayed similarly. .

Next, the operation of the next word search instruction key (1d) will be described. After inputting "Au" and pressing the Kana-Kanji conversion key (1a) to convert "Ai", the result is as shown in FIG.

Here, when the example dictionary key (1b) is depressed, FIG.
Is displayed as follows. When the user wants to see an example corresponding to “breath” of “the breath fits” among the displayed examples, the user moves the cursor using the cursor movement keys as shown in FIG.
Move to the position of "breathing". Here, if the next word search instruction key (1d) is pressed, the operation is performed as shown in FIG.

That is, the word "breathing" is composed of the words "breathing" and "fitting". Then, since this example is displayed as an example of “match” which is a homonym of “meet”, the remaining word “breath” excluding this “match” is detected. Then, an example of the detected word “breath”, its homonym, and an example of this homonym are displayed. Note that, in this example, there is no example of this homonymous word, as shown in FIG.

(B) Description of the second embodiment. A second embodiment of the present invention will be described with reference to FIGS. In the second embodiment, examples are created from a co-occurrence word dictionary. In addition, creating an example from a co-occurrence word dictionary is disclosed in Japanese Patent Application Laid-Open No. 4-28945 (G06F15 / 20).
And is well known.

(B-1) Description of each part of the second embodiment. FIG. 11 is a block diagram of the word processor of this embodiment.
(1) is an input unit composed of a keyboard. This input section
(1) includes various instruction keys such as a character key for inputting a kana character string by a kana input or a Roman character input, a kana-kanji conversion key for instructing a kana-kanji conversion instruction, a cursor movement key, and an example dictionary key.

(2) is a read-only memory (ROM). The ROM (2) stores kana-kanji basic word dictionary data (201), attached word dictionary data (203), first example dictionary data (205), and the like, which are necessary when performing kana-kanji conversion and example reference. (3) is a readable / writable memory (RAM). The RAM (3) has a kana input buffer (301) and a kanji output buffer (30
2) Store the example table (307) and the like.

(4) is a control unit. The control unit (4) is provided with a kana character string and an instruction input from the input unit (1). The control unit (4) controls data transmission and reception of each unit of the device according to the given instruction, and outputs the input character string to an output unit (5) including an LCD display or the like. (6) is a kana kanji control unit that controls kana-kanji conversion.
If the input is a kana character string, the kana-kan control unit (6) stores a reading code string corresponding to the kana character string in a kana input buffer (301) in the RAM (3). Also, as a result of the Kana-Kanji conversion, when the character string mixed with the Kana-Kana is determined, the Kana input buffer (301) is initialized. If the given input is a Kana-Kanji conversion instruction, the word candidate creating section (7), the phrase candidate creating section (8), and the output candidate creating section (9) are sequentially activated.

The word candidate creation unit (7) has a kana input buffer.
The matching of the reading code string stored in (301) with the reading code strings of the Kana-Kan Kanji dictionary data (201) and the Kana-Kan Katakana dictionary data (202) in the ROM (2) is sequentially performed. Then, the data such as the part of speech and the appearance frequency of the word whose reading code string matches are stored in the word candidate table (304) in the RAM (3). At this time, auxiliary word processing is performed using the auxiliary word dictionary data (203) in the ROM (2), and stored in the word candidate table (304).

The phrase candidate creating section (8) includes a word candidate table
Based on the word data stored in (304) and the co-occurrence word dictionary data (204) in the ROM (2), the reading code string stored in the kana input buffer (301) is segmented, and the segmenting data is segmented. It is stored in the candidate table (305). Output candidate creation unit (9)
Uses the phrase data stored in the phrase candidate table (305) to store the word notation code and word management data in the RAM (3).
In the kanji output buffer (302).

(10) is an example reference control unit. The example reference control unit (10) includes a homophone search processing unit (11), an example search processing unit (12), a four-character idiom search processing unit (13), and a homophone output processing unit (1).
5) Activate the example output processing unit (16) and the four-character idiom output processing unit (17). Further, the example reference control unit (10) responds to an instruction from the input unit (1) to output a homophone output buffer (30) in the RAM (3).
9), Example output buffer (310), 4-character idiom output buffer (31
1), transfer data such as notation codes necessary for display stored in the kanji output buffer (302) to the display buffer (303),
Output to the output unit (5). Alternatively, the next word search processing unit (1
4) Activate the selected word output unit (18).

The homophone search processing unit (11) includes a notation code string of a word stored in a kana input buffer (301) and a kanji output buffer (302), a kana-kan basic word dictionary data (201) and a kana Matching with the Han Katakana dictionary data (202) is performed to determine whether the word is a homophone, and the word data that is a homophone is stored in the homophone table (306).

The example search processing unit (12) performs the homophone table (3
06), the co-occurrence word dictionary data (204), the first example dictionary data (205), and the second example dictionary data (206) are searched, and the corresponding word is used as a key. The data of the used example is stored in the example table (307). The next word search processing unit (14) searches the word to be displayed next and its homonymous words from the word data and the example data stored in the homophone table (306) and the example table (307). For example, when the word data indicates “breath” and the example data indicates “match”, the example data “match” indicates that the word data is “breath” and the word data is “match”. This is an example. The remaining word data "go" and its homonyms are generated and output to the homonyms table (306).

The homophone output processing unit (15) includes a homophone table.
For each word data stored in (306), search the Kana-Kan basic word dictionary data (201) and the Kana-kan katakana dictionary data (202), generate the notation code of the corresponding word, and Store in the output buffer (309). The example output processing unit (16) performs, for each example data stored in the example table (307), the kana-kan basic word dictionary data (201), the kana-kan katakana dictionary data (202), and the co-occurrence word dictionary. Data (204), first example dictionary data (205), second example dictionary data (2
06), example priority table (208), example auxiliary word table (209),
It retrieves the inflected word display data (210), generates a notation code of the corresponding example, and stores it in the example output buffer (310).

The four-character idiom search processing unit (17) searches the four-character idiom dictionary data (207) for each word data stored in the homophone table (306), and the corresponding word is used as a key. The example data is stored in the four-character idiom table (308). In addition, the four-character idiom output processing unit (17), for each four-character idiom data stored in the four-character idiom table (308),
Kana-Kan basic word dictionary data (201), four-character idiom dictionary data (2
07), and generates a notation code of the corresponding four-character idiom and a meaning notation code of the four-character idiom, and outputs the four-character idiom output buffer (3
09).

The selected word output processing unit (18) converts word data stored in the homophone table (306), a notation code stored in a kanji output buffer (302) which is a kana-kanji conversion result, word management data, and the like. A notation code for displaying the specified word, word management data, and the like are newly generated and output to the kanji output buffer (302).

(B-2) Description of the operation of the second embodiment. The operation of this word processor will be described. The kana-kanji conversion function will be described below. The example display will be described later (B-2
This is explained in section -2).

(B-2-1) Description of Kana-Kanji conversion operation. When the kana character string "Koibito Ai" is sequentially input from the input unit (1), the control unit (4) activates the kana kan control unit (6) and converts the kana character into the kana input buffer (301). The corresponding read code is stored as shown in FIG. 12 while incrementing the write position.

When a kana-kanji conversion instruction is input from the kana-kanji conversion key of the input unit (1), the kana-kanji control unit (6) outputs a separator indicating the end of the input after the reading code string stored in the kana input buffer (301). The code "0" is written, and the word candidate creation unit (7) is started. The word candidate creation unit (7) reads the read code string “meet the koibito” stored in the input buffer (301).
And the kana / kana katakana dictionary data (202) shown in FIG. 13 and the kana / kana katakana dictionary data (202) shown in FIG.

This comparison is made based on the reading codes of the words in the Kana-Kan Kanji basic word dictionary data (201), the Kana-Kan Katakana dictionary data (202), and the 0th read code sequence in the input buffer (301). Compare with "Meet Koibito", then compare with "Meet Biibi" from the first sequence. . , And the comparison is performed in order from the fifth position in the array, such as “Au”. The kana-kan basic word dictionary data (201) and the kana-kan katakana dictionary data (202) include a reading code string corresponding to a word reading, a notation code string corresponding to a word notation, and a frequency of occurrence of the word. , With parts of speech. Word reading and notation are only the stem excluding the inflected ending part. For example, "meet" means "word reading: a, notation: meeting"
Is stored.

Here, the process until the word candidate "Lover" is stored in the word candidate table (304) will be described below. In the comparison with the `` meet the Koibito '' from the 0th array of the read code string stored in the kana input buffer (301),
A comparison with the kana-kan basic word dictionary data (201) is performed.

Comparing the reading code “Koibito” of the word with the word number 10191 in FIG. 13 with the reading code string “Meets Koibito” stored in the kana input buffer (301), the reading of the word is Is completely contained in the column. Also, since the part of speech of the word with the word number 10191 is a noun and has no inflectional ending, the word candidate table (30) as shown in the array (7) of FIG.
While storing the word candidate data in 4), as shown in FIG. 15, search the attached word data of the attached word dictionary data (203),
The reading code of the attached word part "Ni" following "Koibito" in the kana input buffer (301) is the basic kana-kanji dictionary data
A test is made to see if it is possible to continuously connect to the word "lover" read from (201).

That is, the attached word dictionary data (2
The attached word data that can be connected to the noun in 03) is compared with the reading code string "meet" following the above word candidate. As shown in the auxiliary word dictionary data (203) in FIG. 15, the noun has the auxiliary word "ni".
Exists, the word candidate data with attached words is stored in the word candidate table (304) as shown in array (8) of FIG. 16 (A). Next, Katakana dictionary data for Kana Han (20
The same applies to 2), but in this case, there is no matching data.

The starting point in the word candidate table (304) of FIG. 16 is the starting position of the word candidate reading represented by the array number of the kana input buffer (301). The end point indicates the end position of the reading of the word candidate by the array number of the kana input buffer (301). The part-of-speech and frequency correspond to the appearance frequency and part-of-speech data in the Kana-Kankan basic word dictionary data (201) and the Kana-Kankan katakana dictionary data (202). The attached word length is the length of the attached word portion of the word candidate. The appendix number is grammatical connection information. The word number is a number indicating the number of the word from the beginning of the dictionary in the basic kana-kanji dictionary data (201) and the kana-kan Katakana dictionary data (202). However, Kana-Kan Kanji basic dictionary data (201) and Kana-Kan Katakana dictionary data (20
2), the word number of the Kana-Kankan Katakana dictionary data (202) is a constant 300
Starts from 01.

Next, the word candidate "meet" is stored in the word candidate table.
The process up to the storage at (304) will be described. Similar to the above, in the comparison of the reading code sequence of the input buffer (301) with the sequence of the
01), and sequentially compare with Kana-Kan Katakana dictionary data (202).

When the reading code “A” of the word having the word number 1 shown in FIG. 13 is compared with the reading code string “A” of the input character string, the reading of the word is completely included in the input character string. The part-of-speech of the word “open” with word number 1 has inflectional endings in five lines, so search the attached word dictionary data (203) and test whether the attached word can be connected consecutively to the word. . The attached word data that can be connected to the 5-line utilization of the attached word dictionary data (203) shown in FIG. 15 is compared with the kana character string `` U '' that is continuous with the above word. Since it is not possible to connect to the part-of-speech utilizing the five-row row, the word candidate data with attached words is not stored in the word candidate table (304).

In the comparison with the word number 2 "go" in the kana-kan basic word dictionary data (201), both the comparison with the input character string and the connection test of the attached word are OK, and the arrangement shown in FIG. It is stored in the word candidate table as shown in (14). Next word number 3
Similarly, "kai" is OK for both the comparison with the input character string and the connection test of the attached word.

The word candidates thus stored and the start point, end point,
If data having the same part of speech, adjunct length, and adjunct number already exists in the word candidate table (304), word number 3 is added to the word number data of the matching data as shown in FIG. 16 (B). I do. Finally, a word candidate table (304) as shown in FIG. 16 (C) is created. Kana-kan basic word dictionary data (201),
When the comparison with the Kana-Kan Katakana dictionary data (202) and the storage of the word candidate data in the word candidate table (304) have all been completed, the phrase candidate creator (8) is activated.

The phrase candidate creating section (8) includes a word candidate table
The kana character string stored in the kana input buffer (301) is segmented based on the word candidate data stored in (304). First, word candidates are combined based on the start point data and the end point data of the word candidates, and the phrase cutoff candidates such as "Koibit / meet" and "Koibit / meet". Further, a score (evaluation value) is assigned to a plurality of segmentation candidates according to the reading length, frequency, and the like of each word candidate, and the priority of the segmentation candidates to be output is determined.

FIG. 17 shows a phrase candidate table. Numerical values stored in phrases 1, 2 and the like indicate the arrangement positions of the word candidate table (304) in FIG. 16C. The average phrase length is obtained by dividing the sum of the reading lengths of the combined word candidates by the number of combined word candidates. The average frequency is obtained by dividing the sum of the frequencies of the combined word candidates by the number of word candidates. The value obtained by adding this value is used as the evaluation value.

In the case of "meeting a child", the average candidate length is (5 + 2) /2=3.5, and the average frequency is (8 + 12) / 2 = 10. The evaluation value is a value obtained by adding these values, and is 13.5.
When the storage of the phrase candidate data in the phrase candidate table (305) is completed, the output candidate creating unit (9) is started. The output candidate creation unit (9) outputs the phrase candidate “Koibito ni / Aoi” having the largest evaluation value among the phrase candidates stored in the phrase candidate table (305) shown in FIG. 17 (phrase 1: 8, phrase 2:14) is selected as an output candidate.

FIG. 18 is a conceptual diagram of the co-occurrence word dictionary data (204) used to select a word to be output from the word candidates "koibito ni" and "au" of each phrase. In FIG. 18, word numbers are stored. In FIG. 18, characters corresponding to the word numbers are shown for simplicity of description. Figure
Data of word A and word B as a set in 18 and the word A
And a word form representing the form of a sentence formed by the word B. Word A,
The word B data stores a word number.

First, based on the number (8) of the word candidate corresponding to "Koibito ni", the arrangement of the word candidate table (304) in FIG.
The word number 10191 is obtained from the (8) th. Then, the word numbers 2, 3, and 4 are obtained from the (14) th array in the word candidate table (304) in FIG.
Then, the combination of these word numbers is compared with the co-occurrence word dictionary data (204). [10191: 2], [10191: 3], [10191:
[4] of co-occurrence word dictionary data (204): "# 3"
For the word set of [10191: 3] that matches "1""lover"", it is compared whether the sentence form of these words matches the phrase form of the co-occurrence word dictionary data (204).

If there is a match, the output of these words is given priority. In this case, the relationship between the word “lover” and the word “meet” matches the connection of the word “lover” and the particle “ni” in the phrase form data of the co-occurrence word dictionary data (204). And the word "meet" are given priority, and the notation code and word management data are output to the kanji output buffer (302). The word management data includes the number of output phrases, the number of input kana characters corresponding to each of the phrases, the number of kanji characters, and the number of attached word characters.

As shown in FIG. 19, "meet a lover" is stored in the kanji output buffer (302). Since the phrases are "Koibito ni" and "Ai", the number of phrases is "2". In addition, the number of kana characters in the first phrase is 5 for “Koibito ni”, the number of kanji characters for the first phrase is 3 for “lover”, and the number of adjunct characters for the first phrase is 1 for “ni”. Also, the number of kana characters in the second phrase is stored as 2 for "au", the number of kanji characters is stored for "2", and the number of adjunct characters is stored for "u".
When the storage in the kanji output buffer (302) is completed, the control is returned to the control unit (4), and the data of the kanji output buffer (302) is passed to the output unit (5) for display.

(B-2-2) Explanation of operation of example display. Here, when the example dictionary key of the input unit (1) is input, the control unit (4) activates the example reference control unit (10).

The example reference control unit (10) includes a homophone search processing unit.
(11) The example search processing unit (12) and the four-character idiom search processing unit (13) are sequentially activated. The homophone search processing unit (11) obtains a target word for example reference and its homophone data from the data stored in the kanji output buffer (302) and the kana input buffer (301).
In this embodiment, the end of the clause is set as the target clause, but may be the first clause.

In this process, first, the number of homophones in the homophone table (306) as shown in FIG. 20A is initialized. Then, the head positions of the kana code and the notation code which are the reading of the target word in the respective buffers are obtained. In this case, the target word is "meet" in the second phrase based on the number of phrases stored in the kanji output buffer (302). The head position of the kana code in the kana input buffer (301) and the head position of the notation code in the kanji output buffer (302) are respectively determined from the kana character number data (5) of the first clause of the kanji output buffer (302). 5) of the array of the kanji code buffer (302).
Third. The reading length of the target word is 2, and the kanji length is 2.

Using the word reading “Au”, the basic word dictionary data for kana-kan (201) and the katakana dictionary data for kana-kan (20
2) Search and "meet" the notation of the word whose reading code matches
Compare with As shown in FIG. 13, since only the stem portion of a word is stored in the kana-kan dictionary (201), no matching is performed.

Next, the retrieval is performed by reading the reading code string and the notation code string, excluding the last code of the reading code string and the notation code string. However, if the attached word length is exceeded, no search is performed. That is, the search is performed using the reading “A” and the notation “Kai”. As a result, the word number 3 "me" is obtained. When the search is performed without the attached word portion, whether the attached word portion “U” is connectable is checked using the attached word dictionary data (203) in FIG.

In this example, since "U" can be connected to the U-line 5-row utilization, the check is true, and the part of speech and the word number are stored in the homophone table (306) as shown in FIG. . Furthermore, it is checked whether this part of speech is the target of the example sentence. As a result of this check, if the part-of-speech is unlikely to be included in the example sentence, the last code of the reading code string and notation code string to be searched within the range of the number of attached word characters is further omitted, and the Kana-Kan Kanji basic word dictionary data (201) Search again the Katakana dictionary data for tokana (202).

As a result of this check, if there is a part of speech that may be included in the example sentence, a search for a homonym is performed.
The homophone search is performed by searching the kana-kan basic word dictionary data (201) and the kana-kan katakana dictionary data (202) using the word reading “A”. As shown in FIG. 13, since only the stem portion of a word is stored in the dictionary for kana-kan, there is no data matching “a”.

Next, a search is performed by reading the last word from the reading "a". However, if the attached word length is exceeded, no search is performed. That is, the search is performed with the reading “A”. As a result, the word number 1 of “open” is obtained. If the search is performed without the attached word part, check whether the attached word part "U" is connectable.
This is performed using fifteen attached word dictionary data (203).

In this example, since "U" is not connectable to the use of ka-line 5 columns, the check is false and the kana-kan basic word dictionary data (201) and the kana-kan katakana dictionary data (202) are used. Continue searching. The word number 2 “go (U) [wa row 5 column utilization]” is obtained. The check is true because the attached word part "U" is connectable. Further, since the part of speech is the same as the part of speech in the homophone table and the word number 2 is not already stored in the homophone table (306), the word number 2 is stored and the number of homophones is incremented by one. At this time, if the part of speech is different from the part of speech in the homophone table, the word number is stored in a temporary buffer (not shown).

The basic word dictionary data for kana-kan (201)
The process is repeated until there is no data corresponding to the Tokana Katakana dictionary data (202). Finally, the word number stored in the temporary buffer (not shown) is stored following the already stored word number in the homophone table. Also at this time, it is stored only when the word number to be stored is not already stored in the homophone table (306).

Further, the number of homophones is incremented by the number of the stored word numbers. A homophone table (306) is created as shown in FIG.

Subsequently, the example search processing section (12) is started. First, the example search processing unit (12) executes the example table (307).
Is initialized with constants such as END data and FFFF (H).
As in 23 (A), the word numbers 3, 2, and 4 stored in the homophone table (306) are sequentially stored as the word numbers in the example table (307).

The first example dictionary data (205) and the second example dictionary data (206) are searched for these word numbers. Fig. 21
A conceptual diagram of the first example dictionary data (205) is shown in FIG. The first example dictionary data (205) corresponds to the data of the co-occurrence word dictionary data (204). The data value 0 of the first example dictionary data (205) indicates that the corresponding co-occurrence word dictionary data (204) is not used for example display.

FIG. 22 is a conceptual diagram of the second example dictionary data (206). The second example dictionary data (206) includes a notation code string of an example sentence and a keyword for search. The keyword stores a word number of a word serving as a keyword.

In the case of word number 3, co-occurrence word dictionary data (20
4) The word number data of word A and the word number data of word B are searched, and 10
5,106,107 are obtained. For these word numbers 105, 106, 107, check whether the data value of the first example dictionary data (205) is 0, that is, whether or not to use the example display, and use the co-occurrence word dictionary data (204)
Are stored in the example table (307) as shown in FIG. 23 (B).

In the case of word number 2, co-occurrence word dictionary data (20
4) Search the word number data of the word A and the word number data of the word B, and use the sequence number of the co-occurrence word dictionary data (204) as 77,
78, 79, 80 are obtained. For these word numbers 77, 78, 79, 80, it is checked whether the data value of the first example dictionary data (205) is 0, that is, whether the word value is not used for example display, and the one used for example display is the co-occurrence word dictionary. Data (204)
Are stored in the example table (307) as shown in FIG. 23 (B). In this case, as shown in FIG. 21, since the data value of the first example dictionary data (205) corresponding to the word number 79 is 0,
It is not stored in the example table (307).

Subsequently, it is searched whether or not the keyword of the second example dictionary data (206) has the word number 2, and the second
Sequence numbers 124 and 125 of the example dictionary data (206) are obtained. A constant is added to distinguish from the sequence number of the co-occurrence word dictionary data (204). This constant need only be larger than the maximum sequence number of the co-occurrence word dictionary data (204). In this example, this constant is set to 30000. Therefore, the above SEQ ID NO: 30124
And 30125, which are stored in the example table (3) as shown in FIG.
07).

Similarly, for word number 4, FIG.
An example table (307) is created as shown in FIG.

Subsequently, the four-character idiom search processing unit (13) is activated. The four-character idiom search processing unit (13)
08) with END data and constants such as FFFF (H), and furthermore, as shown in FIG. 24 (A), the word numbers 3, 2, and 4 stored in the homophone table (306) are sequentially converted into a four-character idiom table. (308) is stored in the word number.

The four-character idiom dictionary data (207) is searched for these word numbers 3, 2, and 4. FIG. 25 shows a conceptual diagram of the four-character idiom dictionary data (207). The four-character idiom dictionary data (207)
It consists of a word number of a four-character idiom, a semantic code string of the four-character idiom, and a keyword for searching. The keyword stores a word number of a word serving as a keyword.

First, a search is made for word number 3 and a match is made with the keyword “Chiaki one day”. A four-character idiom table for the sequence numbers of the matched four-character idiom dictionary data (207)
(308). Next, it is searched whether or not the keyword of the four-character idiom dictionary data (207) has the word number 2,
In this case, there is no matching. Then, for word number 4
Even if you search, the four-character idiom table (308) as shown in FIG.
Create

As described above, the homophone table (306), the example table (307), and the four-character dictionary are processed by the homophone search processor (11), the example search processor (12), and the four-character idiom search processor (13). When the creation of the idiom table (308) is completed, the example reference control unit (10)
In order to convert each into a notation code, a homophone output processing unit (15) and an example output processing unit (16) are started.

First, the example reference controller (10) reads out word numbers from the homophone table (306) in order. The first data of the word number is word number 3, and this word number is sent to the homophone output processing section (15). The homophone output processing unit (15) generates and outputs word notation data "meet" based on the word number. A notation code is similarly generated for word numbers 2 and 4, and “match” and “encounter” are indicated by the homophone output buffer (30
Store in order as in 9).

As described above, the example reference control unit (10) sequentially stores the generated data in the homophone output processing unit (15) for each word. The details of the homophone output processing unit (15) will be described below. The homophone output processing unit (15) is stored in the kana-kanji conversion basic word dictionary data (201) or the kana-kanji conversion katakana dictionary data (202) in order to convert the word number into a notation code. Read the notation code of the stem part of the word.

The word "3" is read from the notation data of the word number 3 stored in the phonetic word table (306), and the inflected word "u" is read out from the part-of-speech data and the inflected word display data. Output. When there are a plurality of parts of speech of a word stored in the kana-kanji conversion basic word dictionary data (201) or the kana-kanji conversion katakana dictionary data (202), the part-of-speech data stored in the homophone table (306) is used. Is matched, and the part of speech that matches is given the highest priority. The other parts of speech are stored in the basic word dictionary data for kana-kanji conversion (201) or the katakana dictionary data for kana-kanji conversion (202) in order. Alternatively, the order may be the frequency.

As described above, the notation codes stored in the basic word dictionary data for kana-kanji conversion (201) or the katakana dictionary data for kana-kanji conversion (202) are used in FIG. A notation code to which an inflected word notation code is added is generated based on the word notation data.

Next, when there is a part of speech to be processed, the inflected word data is added by the inflected word notation data in FIG. 29 based on this part of speech, and the generated notation code matches the already generated notation code. It is verified that no notation is made, a midpoint notation code “·” is added, and thereafter the notation code generated in the same manner as above is added.

If it matches the one stored in the output buffer, the next part of speech to be processed is processed. This processing outputs a notation code when all the parts of speech of the words stored in the Kana-Kanji conversion basic word dictionary data (201) or the Kana-Kanji conversion Katakana dictionary data (202) are completed.

The processing when there are a plurality of parts of speech of this word will be described. Basic word dictionary data for kana-kanji conversion (20
Like the part of speech of word number 16 "love" stored in 1),
There are several "nouns", "suffixes" and "sa-various nouns"
The case where the part of speech data of (306) is "sa noun" will be described.
From the notation data of the words stored in the basic word dictionary data for kana-kanji conversion (201), "Love" is stored in the homophone output buffer, and stored in the homophone table (306). The "sa-noun" in the basic word dictionary data (201) is processed with the highest priority, and "to" is additionally stored in the homophone output buffer (309) from the inflected word notation data of FIG.

Next, since there is no kana data to be added to the part of speech "noun" to be processed, the data to be stored in the homophone output buffer (309) is "love", and
Since it is not the same as the data "love" stored in (309), it is additionally stored in the homophone output buffer (309).
Subsequently, the part of speech “suffix” to be processed has no kana data to be added, the data to be stored in the homophone output buffer is “love”, and the data stored in the homophone output buffer (309) is “love”. Since the same word is already stored as compared with “Love”, the notation code is not stored in the homophone output buffer (309).

Thus, the processing is completed for all parts of speech of the word “love”, and the notation code stored in the homophone output table is “love / love”, which is output. Homophone output section
When the processing of (15) ends, the example output processing unit (16) is started. In this example output process (16), the example table (307)
The notation code is generated based on the example numbers stored for each word, and the data is stored for each word in the example output buffer (310) as shown in FIG.

That is, according to the example table (307) in FIG. 23, the first example of the word to be displayed first is the example number 105, and this example number is sent to the example output processing unit. The example output processing unit generates and outputs a notation code “meet a lover” based on the example number 105. The output notation code is stored in the example output buffer (310) for each example of each word as shown in FIG. This process is performed for all the example numbers stored in the example table (307).

Hereinafter, the example output processing section (16) will be described in detail. Note that this description is based on the operation for the second displayed word. The first example of the word to be displayed second is the example number 77 from the example table (307) in FIG. Upon receiving the example number 77 from the example reference control unit (10), the example output processing unit (16) determines whether the example is the example of the first example dictionary data (205) or the example of the second example dictionary data (206) according to the example number. Judge. That is, if the example number is less than 30,000, it is an example of the first example dictionary data (205), and if it is 30,000 or more, it is an example of the second example dictionary data 206.

Since the example number 77 is less than 30,000, the first
A notation code of the example is generated based on the example dictionary data (205). Hereinafter, generation of a notation code of an example based on the first example dictionary data (205) will be described. Example output processing unit
(16) is the example number 77 from the co-occurrence word dictionary data (204).
Read the data of the number.

The co-occurrence word dictionary (204) is composed of a set of word numbers and phrase form data.
(U) '' and word number 1142 for the word `` breath '',
The data of the phrase form "B does A" is obtained. The first example dictionary data (205) is associated with the co-occurrence word dictionary data (204), and indicates which data of the phrase form data in the corresponding co-occurrence dictionary data is used for the example display. This is represented by the order of the phrase form data when arranged in the order of priority in the example priority table (208) as shown in FIG.

That is, if the first example dictionary data (205) is 0
In this case, the example of the corresponding co-occurrence dictionary data (204) is not displayed. A value of 1 indicates the phrase form data having the first priority when arranged in the priority order of the example priority table among the phrase form data of the co-occurrence dictionary data. In the case of the example number 77, as shown in FIG. 21, the value of the first example dictionary data (205) is 1, and the corresponding co-occurrence word dictionary (20
Since the phrase form data of 4) is "B does A", the phrase form data used for example display is "B does A".

By the way, the example attached word table (20
The order / reverse data of 9) indicates the order of words A and B. That is, if the form data “A does B”, the order is “0”, and if the form data “B does A”, the order is “1”. Next, the example auxiliary word table of FIG.
Since the order / reverse data indicating the order of the words A and B of the phrase form data “B does A” in (209) is 1 indicating the reverse, the word number 1142 of the word B in the co-occurrence word dictionary (204) To the notation code.

The notation code "breath" of the word number 1142 is obtained from the kana-kanji conversion basic word dictionary data (201). Subsequently, the notation code "GA" is added from the attached word data of the example attached word table (209), and the notation code "go" of the word number 2 obtained from the kana-kanji conversion basic word dictionary data (201) is added. Add.

Further, a vocabulary word "U" of the part-of-speech word number "2" obtained from the vocabulary word notation data of FIG. 29 is added to generate an example notation code "breath fit". ,Output.
Also, as in the case of the word number 30124, the second example dictionary data (206)
When the notation code of the example is obtained based on the word number, 124 obtained by subtracting 30000 from the word number is obtained, and from this value, the 124th example sentence notation code of the second example dictionary data (206) `` water does not match ''
Is output.

As described above, when the storing of data in the homophone output buffer (309) in FIG. 26 and the example output buffer (310) in FIG. 27 is completed, the example reference control unit (10) performs display.
When displaying the homophone, it is checked whether or not a four-character idiom exists for the word using the data of the four-character idiom table (308). If there is a four-character idiom, the same phonetic word is enclosed in “★” and “★”, and if there is no four-character idiom, it is enclosed in “[”, “]”.

To display a homophone, a homophone output buffer (30
Use the data of 9). Following the display of the homophone, three examples corresponding to the word are displayed. If there are four or more examples, "O" is displayed at the beginning of the line where three examples are displayed, indicating that the examples could not be displayed on one screen. Means for displaying an example that cannot be completely displayed by a key operation for switching the display of the example list or the like will be omitted.

When the display of the first homophone and the example is completed, the same homophone and the third homophone are displayed in the same manner, and the display of FIG. Such a display is made, and a key input wait state is set. Further, the cursor can be moved to a homophone portion and an example portion in response to an input of a cursor key, and cursor control is performed by associating a cursor position with a homophone output buffer and an example output buffer.
In other words, from the cursor position, the classification of the homophone or the example and the word number of the homophone or the example number of the example are obtained.

(B-2-3) Four-character idiom display processing. Next, a four-character idiom search will be described using a specific example.
As shown in Fig. 32 (A), the homonyms "meet" enclosed by "★" and "★"
When the four-character phrasal word search key is input when the cursor is at, the example reference control unit (10) sends the word number 2 obtained from the cursor position to the four-character phrasal word output processing unit (17).

The four-character idiom output processing unit (17) generates and outputs word notation data “Chiaki one day” and semantic notation data “The more a day feels like a millennium” from word numbers. The example reference controller (10) stores the output four-character idiom data and semantic notation data in the four-character idiom output buffer (311), and displays the four-character idiom and semantic notation as shown in FIG. 33. Area (5
Control to display in b).

The four-character idiom output processor (17) searches the word number data of the four-character idiom table (308) to obtain a four-character idiom number 99 corresponding to the word number 2. Four-character idiom dictionary data (2
Based on the 99th word number 1528 in 07), the four-letter idiom word notation code `` Chiaki one day '' from the Kana-Kankan basic word dictionary data (201)
Get. In addition, it obtains semantic notation data from the 99th semantic notation data of the four-character idiom dictionary data (207), such that "a day can be felt for a thousand years ..." and outputs these.

(B-2-4) Additive word processing at the time of writing. Next, the writing of a homophone word will be described using a specific example. When the execution key is pressed while the cursor is on the homophone `` fit '' as shown in FIG. 32 (B), the example reference control unit (10) selects the word number 2 obtained from the cursor position and selects the word output processing unit ( Send to 18).

The selected word output processing unit (18) generates and outputs a notation code by synthesizing the word with a kana-kanji converted and output attached word. The output notation code is displayed after being converted to a character string displayed by converting the kana to kanji. In the selected word output processing unit (18), the word number is stored in the kana-kanji conversion basic word dictionary data (201) or the kana-kanji conversion katakana dictionary data (202) in order to convert the word number into a notation code. Read the notation code of the stem of the word. The notation code "go" is obtained from word number 2. Number of adjunct characters in the second clause of the kanji output buffer (302) is 1
, The notation code “u” of the attached word portion extracted from the tail stored in the notation code buffer is added, and the notation code “matches” is output.

(B-2-5) Next word search processing. Next, the next word search process will be described using a specific example.
When the cursor is moved and the next word search instruction key (1d) is input while the cursor is at the example "Breath fit" as shown in FIG. 32 (C), the example reference control unit (10) is obtained from the cursor position. The example number 77 and the word number 2 are sent to the next word search processing unit (14).

The next word search processing unit (14) determines that the example number is 3000
If it is less than 0, the first example dictionary data (205) is searched, and if it is 30,000 or more, the second example dictionary data (206) is searched. Since the sent example number is 77, the first example dictionary (205) is searched. As shown in FIG. 21, the first example dictionary (205) is a co-occurrence word dictionary.
(204), and the 77th word group data “# 2, # 1142” of the co-occurrence word dictionary (204) can be obtained from the example number 77.

From this data and the sent word number 2, a word number 1142 to be searched next can be obtained.
Next, the word notation code “breath” and the word reading code “iki” stored in the kana-kanji conversion basic word dictionary data (201) corresponding to the word number 1142 are obtained. Next, FIG.
The initialization of the number of homophones in the homophone table (306) as shown in FIG.

Using the word reading “iki”, the kana-kan basic word dictionary data (201) and the kana-kan katakana dictionary data (20
2) Search and compare the notation of the matched word with "breath". Hereinafter, matching is performed in the same manner as in the homophone processing unit (11). Figure 34
As in (B), word number 1142 "breath", word number 1142 "spirit",
The word number 1151 “Abandon” is obtained as a homophone and stored in the homophone table (306).

Thereafter, similarly to the above processing, the example reference control unit (10) includes the example reference search unit (11) and the four-character idiom search processing unit.
(12) The homophone output processing unit (15) and the example output processing unit (16) are activated, and the display shown in FIG. 35 is performed.

In the first and second embodiments, the identification is displayed at the time of displaying the example. However, the present invention is not limited to this, and the identification and display may be performed at the time of displaying a kana-kanji conversion candidate.

Further, in the second embodiment, the next word is searched using the co-occurrence word dictionary, but the present invention is not limited to this.

In the first and second embodiments, the search for the next word is performed using the next word search instruction key (1d). However, this may also be used as the example dictionary key (1b). That is,
When the example dictionary key (1b) is pressed while the cursor is on the example, the example dictionary key (1b) may operate as the next word search instruction key (1d) of the present embodiment.

[0113]

According to the present invention, by changing the display form in advance, it is possible to inform the user of the presence of a related idiom, giving a user who does not know the idiom an opportunity to use the idiom display function, and Provide an environment where words can be selected.

[Brief description of the drawings]

FIG. 1 is a diagram showing an appearance of a first embodiment of the present invention.

FIG. 2 is a flowchart showing the operation of the first embodiment.

FIG. 3 is a diagram for explaining the screen contents of the first embodiment.

FIG. 4 is a diagram for explaining the screen contents of the first embodiment.

FIG. 5 is a diagram for explaining the screen contents of the first embodiment.

FIG. 6 is a diagram for explaining the screen contents of the first embodiment.

FIG. 7 is a diagram for explaining the screen contents of the first embodiment.

FIG. 8 is a diagram for explaining the screen contents of the first embodiment.

FIG. 9 is a diagram for explaining the screen contents of the first embodiment.

FIG. 10 is a diagram for explaining the screen contents of the first embodiment.

FIG. 11 is a block diagram of a second embodiment of the present invention.

FIG. 12 is a diagram for explaining a kana input buffer according to the second embodiment.

FIG. 13 is a diagram for describing kana-kan basic dictionary data of the second embodiment.

FIG. 14 is a view for explaining katakana katakana dictionary data of the second embodiment.

FIG. 15 is a diagram for explaining attached word dictionary data according to the second embodiment.

FIG. 16 is a diagram illustrating a word candidate table according to the second embodiment.

FIG. 17 is a diagram illustrating a phrase candidate table according to the second embodiment.

FIG. 18 is a diagram for explaining co-occurrence word dictionary data according to the second embodiment.

FIG. 19 is a diagram illustrating a kanji output buffer according to the second embodiment.

FIG. 20 is a diagram for explaining the same sound table of the second embodiment.

FIG. 21 is a diagram for explaining first example dictionary data of the second embodiment.

FIG. 22 is a diagram for explaining the second example dictionary data of the second embodiment.

FIG. 23 is a diagram for explaining an example table of the second embodiment.

FIG. 24 is a diagram for explaining a four-character idiom table of the second embodiment.

FIG. 25 is a diagram for explaining four-character idiom dictionary data of the second embodiment.

FIG. 26 is a diagram for explaining the homophone output buffer of the second embodiment.

FIG. 27 is a diagram for explaining an example output buffer of the second embodiment.

FIG. 28 is a diagram for explaining a four-character idiom output buffer according to the second embodiment.

FIG. 29 is a diagram for explaining inflected word notation data according to the second embodiment.

FIG. 30 is a diagram illustrating an example priority table according to the second embodiment.

FIG. 31 is a diagram for explaining an example accessory word table of the second embodiment.

FIG. 32 is a diagram showing display contents in an example display area of the second embodiment.

FIG. 33 is a diagram showing a four-character idiom display of the second embodiment.

FIG. 34 is a diagram showing a homophone table of the second embodiment.

FIG. 35 is a diagram showing an example display state of the next word of the second embodiment.

FIG. 36 is a flowchart showing the operation of the first embodiment.

[Explanation of symbols]

 (1) Keyboard (input unit), (1a) Kana-Kanji conversion key, (1b) Example dictionary key, (1c) Four-character idiom search key (idiom display instruction means), (1d) Next word search instruction key (example instruction means ), (308) Four-character idiom table (search results), (4) Control part, (5) Output part (display means), (5a) Example display area, (5b) Four-character idiom display area, (6) Kana Kan control unit (Kana-Kanji conversion means) (9) Output candidate creation unit, (10) Example reference control unit (Example display means), (11) Homophone search processing unit, (12) Example search processing unit, (14) Next Word search processing unit (next word detection means), (16) example output processing unit, (17) four-character idiom search processing unit (related idiom search means).

 ──────────────────────────────────────────────────続 き Continued on the front page (72) Inventor Tsutomu Tanaka 2-18-18 Keihanhondori, Moriguchi-shi, Osaka Sanyo Electric Co., Ltd. (72) Inventor Takayuki Kowada 2-18-18 Keihanhondori, Moriguchi-shi, Osaka Sanyo Inside Electric Co., Ltd. (72) Inventor Masanori Ito 2-18 Keihanhondori, Moriguchi-shi, Osaka Sanyo Electric Co., Ltd. F-term (reference) 5B009 MB21 ME15 MH07

Claims (2)

[Claims] 1. A document processing apparatus for displaying a phrasal word related to an input word, comprising:
(17), when displaying the homonym, the related idiom search means (17)
Identification display means for displaying together with the search result (308) of the above, and for identifying and displaying the presence or absence of a phrase related to the homophonic meaning word
(10) A document processing apparatus comprising: 2. The document processing apparatus according to claim 2, further comprising a idiom display instruction means (1c) for displaying the idiom associated with the identified homonymous word.