JPS60124769A - Word extracting system - Google Patents

Abstract

PURPOSE:To attain high speed retrieval of a word including a Kanji (Chinese character) by registering Kanji sounds having two or more character readings, using them, sectioning an input Kana (Japanses syllabary) character and forming a character string to be retrieved based on the classification as the forming of the result. CONSTITUTION:The Kana character string inputted from a keyboard input section 1 is stored in an input character string temporary storage section 2 and fed to a Kanji sound processing section 3. The Kanji sound processing section 3 has a classification module and a register, classifies the result of processing according to the condition and transmits the result to a retrieved character string forming section 4. The retrieved character string forming section 4 sets six characters started from a set analysis start position to the buffer. This content and that of a Kanji sound table 5 in which Kanji sounds having two or more character readings are registered are subject to matching processing, the string is sectioned at an element level of the Kanji sound and the result is set to other buffer. Fromg the result of the comparison between the said buffer and the classification register, only the charfacter number's corresponding to the input character string is cut-out to form a retrieved character string.

Description

[Detailed Description of the Invention] Technical Field The present invention relates to a word extraction method in a Japanese word processor, etc., and in particular to introducing the concept of kanji sounds into the term extraction process and setting the search string to the minimum necessary when searching in a dictionary. The present invention relates to an edict extraction method that can reduce erroneous analysis and improve dictionary search speed by not extracting unnecessary candidates.

Prior Art In conventional kana-kanji conversion processing devices, the algorithm for extracting words from input kana character strings is generally
It was something like this:

(1) Setting the analysis start position for a character string Except for special cases, generally the first character (first character) of a character string is set as the start position for analysis, and words whose first character is at that position If the word segmentation is successful, then the first character of the character string after word segmentation is set as the starting position for a new analysis.

(Example) Dango's ~ ↑: First analysis star 1 ~ position Here, if you succeed in getting 9 of "Kaiseki (analysis)", the result will be as follows.

A dumpling from a piece of rice cake ~ ↑: Next analysis start position (2) Creating a search string for the word 7 search lI+?
Assuming that the length of the reading in the calligraphy is a maximum of 6 characters, the following character string to be searched is set in the case of the example sentence "-".

a) Extract the first word (?) Extract the word after successful extraction (4) Extract the word after successful extraction. Extraction of candidates by matching the searched string set in (3) with the header string in the dictionary In the above example, it would be as follows.

Cannot extract candidates with (] + r kaiseki yo) ■ Candidates cannot be extracted with ``kaiseki'' ■ Extract ``Kaiseki'', ``Analysis'', and ``Kaiseki'' with ``kaiseki'' ■ Extract candidates with ``kaiseki'' Extracts “kai”, “kai”, “kai”, “kai”, etc. by “kai” of “cannot do” (extracts “possible”, “ka”, “mosquito”, “section”, etc. by ΦFka) (4 )(3)
Various evaluations were performed on the candidate group extracted in .

and determine the most suitable candidate.

However, the word extraction method described above may extract an extremely large number of candidate groups depending on the human character string.
There is a problem that it causes erroneous analysis and low dictionary search speed.

The present invention was made in view of the above two circumstances, and its purpose is to solve the above-mentioned problems in conventional word extraction methods, reduce erroneous analysis, and improve the speed of dictionary searches. The purpose of this invention is to provide a word extraction method that makes it possible.

Configuration Hereinafter, the configuration of the present invention will be explained in detail based on examples.

FIG. 1 is a block diagram showing an overview of a kana-kanji conversion processing apparatus according to an embodiment of the present invention, and FIG. 2 shows a part of the contents of a kanji cylinder table, which is the main part thereof. In Fig. 1, 1 is a human power unit for keyboard 1, 2 is a human power character string temporary storage unit, 3 is a kanji sound processing unit, 4 is a searched character string creation unit, 5 is a kanji cylinder table storage unit, and 6 is a dictionary search unit. Part, 7
indicates a word dictionary. Please note that Figure 2 is for illustration only.
This is an example of a kanji cylinder table, and the present invention should not be limited to this.

The kanji sound processing unit 3 has a classification module for classifying processing results according to conditions described later and a register for holding the classification results. below.

This register is called "rTYPE".

Hereinafter, the operation of this embodiment will be explained, or the first explanation will be given using the same example sentence as previously shown in the section of the prior art.

The searched character string creation unit 4 stores six characters starting from the analysis star 1 position set in the same way as in the conventional case into a buffer previously set for M (see FIG. 3). This buffer may be one that can one-dimensionally store six characters, and hereinafter this buffer will be referred to as [vJINDOWJ].

Next, the character strings in the above W T, N D OW and the second
Perform ma-notching processing with each element of the kanji cylinder table shown in the figure, and add fJ' to the character string in WINDOW!
Separate the letters and sounds at the element level, and set the results to <nofa, etc., prepared in advance in a way that can be expressed concretely. Here, a buffer called WINDOW2 is prepared, which is expressed as an array with size 6 in the - dimension.

FIG. 4 shows an example of the delimiters applied to the character strings in "W I N +) OW" and the contents of WTNI) OW2. The arrow marked ``WINL)OW'' indicates the separation between the above kanji sounds and the bell, and the number that is the content of WINDOW2 indicates that the kanji sound corresponding to the number of characters exists in the kanji sound table. It is.

here.

WINL) O'TV2 (1) = 2 (corresponds to "rkai") WINDOW2 (2) = 2 (corresponds to "r cough") W
I NDOW2 (3) = 1 - (corresponds to 'ni')
WINDOW2 (4) = 1 (corresponds to “ryo”) WI
NDOW2(5)=O WINDOW2(6)=0.

The results of the above processing are classified according to the following conditions.

(]) WINDOW2(1)≧2, and WINL)OW
If 2(2)≧2, set “1” to TYPE. .

(2) WINDOW2(1)≧2 and WINDOW
2 (2) = ] If TYPE is set to “Seso 1- 2J.

(3) WINDOW2(1)=], and WINDOW2
(2) If ≧2, set "3" to TYPE to seso1.

(4) In cases other than the above categories (1) to (3), enter “TYPE”.
4" to 1-.

Thereafter, a searched character string is created in the following manner according to the above classification results.

If any of the characters from "1" to T3J is set in TYPE, the number of characters corresponding to WINDOW2 (1) + WIN, WINDOW2 (2) and WINDOW2 (1) are extracted from the input character string. , and create two types of searched character strings.

In the case of the example sentence above, the code YPE is "1", so
As the character string to be searched, the following two characters are set: ('L), (2), and (2). Using this searched character string, a dictionary search is performed in the same manner as before.

Note that when T'YI)E is "4", the searched character string is created in exactly the same manner as the conventional method.

Specific examples of each classification are given in FIGS. 5(Δ) to (D) to supplement the explanation. (A) is classification 1 (1'YI)IE= ])
.

(+3) is classified ■('1"Y l) IΣ=2),...
...corresponds to each. The input sentence and searched character string in each case are: (A'): Daigaku de (University) (1-) Daikaku (Kadai (B): Ryakugi de (abbreviation)) In the case of Nakariyakuza (C): Kanonabaai (if possible) (-!)
In the case of kanou t 匈ka (D): Do it like this (same as left) 0) Do it like this.

like this ■Like this (Kokonoyo (Kako smoke) becomes.

In each of the above embodiments, W I N D OVT'
, t; and WINDOW2 are all buffers with a size of 6 characters, but this is not necessarily limited to 6 characters. Also,”-Konmi WT Sa 11-)
Instead of a buffer like OW, input string can be seso1-
It is also possible to provide a buffer to be stored, a plurality of pointers indicating positions in the buffer, and registers that store the values of the pointers.

Effects As described above, according to the present invention, candidate words are extracted using kanji sounds when performing [shiba, rll, and appearance], so that words containing kanji can be extracted at high speed. This has the remarkable effect of being able to transform

[Brief explanation of the drawing]

FIG. 1 is a block diagram showing an embodiment of the present invention, FIG. 2 is a diagram showing part of the contents of a kanji sound table, FIG. 3 is a diagram showing an example of the contents of an input character string buffer, and FIG. 5 is a diagram showing a situation in which an input character string is matched with the contents of a kanji sound table, and FIG. 5 is a diagram showing a specific processing example. 1: Keyport input section, -2=Large input character string temporary storage section,
3: Kanji sound processing unit, 4: Searched character string creation unit, 5: Kanji sound table storage unit, 6 = Dictionary search unit, 7: Word dictionary. Patent applicant Ricoh Co., Ltd. -- Figure 1 Figure 3 Figure 8184 Figure 5

Claims (1)

[Claims] (1) A word dictionary storage means for storing a plurality of words in correspondence with character strings representing their pronunciations, a means for temporarily storing input kana character strings, and a word dictionary storage means for storing a plurality of words in correspondence with character strings representing their pronunciations; and means for temporarily storing input kana character strings; A kana-kanji conversion processing device comprising a means for searching, a table storage means in which kanji sounds having readings of two or more characters are registered, a means for dividing the input kana character string using the kanji sounds, and processing by the dividing means. 11. A 113-word extraction method characterized in that a means for morphologically classifying results is provided, and a character string to be searched is created based on the classification result by the classification means.