JP2011134021A - Character string predicting program and information processing apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To quickly predict a following character string requested by a user regardless of whether an input character string includes Chinese characters or the like by suppressing the increase of the load of retrieval processing while effectively using a limited storage region or an existing dictionary. <P>SOLUTION: When a character string recognized by a character recognition part retrieval part includes any character string other than Kana, a retrieval part retrieves the character string of Kana corresponding to the character string other than Kana from among Chinese character indexes, and retrieves block identification information corresponding to the retrieved character string of Kana from among Yomi indexes, and retrieves the notation of the character string corresponding to the retrieved character string of Kana from among the blocks of a dictionary data part designated by the retrieved block identification information. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a character string prediction program and an information processing apparatus having a function of predicting a character or character string desired by a user.

  2. Description of the Related Art Conventionally, in a personal digital assistant (PDA), as a character input method, a character string is input by handwriting using a stylus pen or the like on a touch panel (hereinafter referred to as “handwriting input method”). The one that adopted was common. Thereafter, as seen in mobile phones, a method of pressing down a dial key (ten key) to which individual characters are assigned or a QWERTY keyboard (hereinafter referred to as a “key press input method”) is generally used. As it turns out, the input of character strings by the “handwriting input method” has become less used. The reason is as follows.

  For devices that use the “key press input method”, the user wishes based on the converted character or character string, for example, in addition to conversion processing that converts the input kana character or character string into a single kanji or single phrase. "Predictive transformation" that predicts a part of a sentence that will be, or after confirming a part of a predicted sentence, "Federated prediction" that further predicts a part of a sentence that the user would want to follow "Conversion" was realized, and the desired text could be created quickly and easily with few key operations.

  On the other hand, devices that adopt the “handwriting input method” generally, for example, when a character string mixed with kanji (character string including kanji and hiragana) is input, “Predictive transformation” was not easily performed. For this reason, every time a user inputs a kanji by hand, the user must perform a process of determining a recognized character or a process of determining after selecting a character. did not become.

  Patent Document 1 discloses a character string prediction method for predicting a character string of a Chinese character desired by a user from an input Chinese character in a “handwriting input method” device. Patent Document 2 discloses a “character string prediction unit” that predicts a subsequent character string from input kanji and the like, and a “kana-kanji character” that is converted to a character string that includes kanji when the predicted character string is hiragana. A character string prediction device including a “conversion unit” is disclosed.

JP-A-9-16586 (FIGS. 1-7, etc.) JP-A-8-255158 (FIG. 3, FIG. 4 etc.)

  The techniques of Patent Documents 1 and 2 described above show application to a “handwriting input method” device, but have the following problems.

  In the technique of Patent Document 1, since it is necessary to search the entire dictionary in order to obtain a predicted character string from an input character string, the CPU processing is occupied, and the CPU clock frequency of a portable information terminal or the like is increased. In the case of a low embedded device, it takes a long time to obtain a search result as compared with a device of “key press input method”, and as a result, the input operation becomes slow.

  On the other hand, in the technique of Patent Document 2, when a character string input by the “handwriting input method” is, for example, hiragana, a search is performed using both the functions of “kana-kanji conversion unit” and “character string prediction unit”. Therefore, as in the case of Patent Document 1, in the case of an embedded device that occupies CPU processing and has a low CPU clock frequency, such as a portable information terminal, the search result is obtained as compared with a “key press input method” device. Takes a long time, and as a result, the input operation becomes slow. Furthermore, in the technique of Patent Document 2, since each of the “kana-kanji conversion unit” and the “character string prediction unit” has a dictionary, in the case of an embedded device having a capacity limit in the ROM area such as a mobile phone, There is a possibility that this ROM area is compressed by a dictionary.

  The present invention has been made in view of the above circumstances, and while effectively using a limited storage area and a dictionary having the same structure, an increase in the load of search processing is suppressed, and an input character string includes kanji and the like. It is an object of the present invention to provide a character string prediction program and an information processing apparatus capable of quickly predicting a subsequent character string desired by a user regardless of whether or not.

  A character string prediction program according to an aspect of the present invention is a computer including an input device capable of inputting a character string by handwriting, a storage medium for storing information, and a display device for displaying information on a screen. Including information that associates notation of a character string including characters other than kana with a kana character string indicating at least a part of reading or heading of the character string, the kana character strings are arranged in code order, and the information is encoded A dictionary data section that is divided into a plurality of blocks in the order of arrangement, and 2) at least a part of the kana character string included in the dictionary data section and a character string other than kana are associated with each other A first index in which a character string other than the kana is arranged in code order, and 3) block identification information designating a block of the dictionary data portion and the identification information. Storage processing for storing, in a predetermined storage area of the storage medium, a second index that includes information in association with a kana character string located at the head of a block and in which the kana character string is arranged in code order A function, a recognition function for recognizing a character string input by the input device, and a character string other than kana included in the character string recognized by the recognition function. A kana character string corresponding to a character string other than the kana character string is searched, block identification information corresponding to the searched kana character string is searched from the second index, and the searched block identification information is further searched. The character string recognized by the recognition function is searched for the notation of the character string corresponding to the searched kana character string from the block of the dictionary data portion specified by When a character string other than kana is not included and a kana character string is included, a block corresponding to the kana character string from the second index without using the first index A search function for searching for identification information, and further searching for a notation of a character string corresponding to the character string of the searched kana from among the blocks of the dictionary data portion specified in the searched block identification information; and the search function This is a character string prediction program for realizing a display processing function for displaying on the screen of the display device as candidates the notation of the character string searched for.

  According to the present invention, while effectively using a limited storage area and a dictionary having the same structure, an increase in the load of search processing is suppressed, and the user can determine whether the input character string includes kanji or the like. It is possible to quickly predict the desired subsequent character string.

The figure which shows an example of a structure of the information processing apparatus which concerns on one Embodiment of this invention. The figure which shows the example of operation | movement, such as prediction conversion on the screen of a display apparatus at the time of inputting "Kanji" by handwriting. The figure which shows the example of operation | movement, such as prediction conversion on the screen of a display apparatus at the time of inputting "Hiragana" by handwriting. The figure which shows the example of operation | movement, such as predictive conversion on the screen of a display apparatus at the time of inputting "Kanji and Hiragana" by handwriting. The conceptual diagram which shows an example of operation | movement of the search by a search part. The figure which shows the example of the data structure of the dictionary data part of various dictionaries in tabular form. The figure which shows the structural example of a kanji index in a table format. The figure which shows an example of a prediction conversion candidate output screen. The figure which shows the detailed example of a prediction dictionary in tabular form. The figure which shows the detailed example of a basic dictionary in tabular form. The flowchart which shows an example of the operation | movement which concerns on prediction conversion candidate display. The flowchart which shows an example of the operation | movement which concerns on the display of the prediction conversion candidate by a kana prediction process. The flowchart which shows an example of the operation | movement which concerns on the display of the prediction conversion candidate by a Chinese character prediction process.

Hereinafter, an embodiment of the present invention will be described with reference to the drawings.
It should be noted that the “character string” referred to in the present specification may have only one character. “Kana” refers to hiragana or katakana. “Non-kana” indicates not only kanji, numbers, and alphabets but also symbols and special characters.

  FIG. 1 is a diagram illustrating an example of a configuration of an information processing apparatus according to an embodiment of the present invention. FIG. 1A illustrates an example of a hardware configuration of the information processing apparatus, and FIG. 1B illustrates an example of a software configuration as a computer program installed in the information processing apparatus.

  The information processing apparatus illustrated in FIG. 1A corresponds to a device suitable for implementation as an embedded system, such as a mobile phone or a portable information terminal, and substantially operates as a computer that executes a program. To do. The information processing apparatus includes a control device 1, a nonvolatile storage device 2 </ b> A, a volatile storage device 2 </ b> B, an input device 3, a display device 4, and an I / O device 5. These elements are connected to each other by a bus 10.

  The control device 1 corresponds to a processor such as a CPU, for example, and controls the entire device. For example, the control device 1 reads a program or data stored in the nonvolatile storage device 2A, or loads the read program or data into the volatile storage device 2B to execute various processes. Further, for example, the control device 1 transmits / receives data input through the input device 3 and data output to the display device 4 to / from the nonvolatile storage device 2A, the volatile storage device 2B, or the external I / O device 5. Or a process of storing data acquired from an external network through the external I / O device 5 in the nonvolatile storage device 2A or the like.

  The nonvolatile storage device 2A corresponds to a rewritable semiconductor memory such as a flash memory or a hard disk drive. The nonvolatile storage device 2A stores data including a character string prediction program according to the present embodiment and various dictionaries and indexes (described later) used by the program.

  The volatile storage device 2B corresponds to a semiconductor memory such as a RAM. The volatile storage device 2B is used as a work area of the control device 1 and stores programs and data loaded from the nonvolatile storage device 2A.

  The input device 3 is disposed on the display device 4 and forms a pen tablet or a touch panel. By performing an operation of drawing a character while pressing a stylus pen or a fingertip within a predetermined area on the pen tablet or touch panel, input of a handwritten character or character string is achieved. In this embodiment, a case where input is performed using a stylus pen on a pen tablet will be described as an example.

  The display device 4 is, for example, a liquid crystal display device, and displays handwriting of characters input by handwriting through the input device 3 in the first display region, or character string candidates recognized after input in the second display region. Or a character string automatically or manually selected from the candidates is displayed in the third display area, or a character string predicted by the user based on the displayed character string is displayed. Or display in the fourth display area.

  The I / O device 5 downloads a dictionary or the like through an external network and sends it to the nonvolatile storage device 2A.

  FIG. 1B shows a character string prediction program and data storage unit stored in the nonvolatile storage device 2A. The character string prediction program includes a storage processing unit 31, a character recognition unit 32, a search unit 33, a prediction candidate output unit 34, a display order processing unit 35, a dictionary editing unit 36, and a display processing unit 37. As each storage unit of data used by the character string prediction program, a character recognition dictionary information storage unit 21, a basic dictionary information storage unit 22, a prediction dictionary information storage unit 23, a learning dictionary information storage unit 24, an index information storage unit 25, A prediction candidate information storage unit 26 is provided. In addition, although not shown, a user dictionary information storage unit, a download dictionary information storage unit (hereinafter referred to as “DL dictionary storage unit”), and a cooperative prediction dictionary storage unit are provided. Note that the same storage unit (storage area) is secured for the data in these storage units when they are loaded into the volatile storage device 2B.

  The storage processing unit 31 uses the non-volatile storage device 2A from 1) a character string including “other than kana” (for example, a character string including a kana including “other than kana” and a character string including only “other than kana”. ) And the kana character string indicating at least a part of reading or heading of the character string, the kana character string is arranged in code order, and the information is arranged in the arrangement direction of the code order. A dictionary data part divided into a plurality of blocks, and 2) information in which at least a part of the character string included in the dictionary data part is associated with a character string “other than kana” from the beginning. And a first index (hereinafter referred to as “kanji index”) in which character strings other than the kana are arranged in code order, and 3) block identification information (block number) designating a block of the dictionary data portion Concerned A second index (hereinafter referred to as “yomi index”) that includes information in association with a kana character string located at the head of a block specified by different information and in which the kana character string is arranged in code order. ) And is loaded and stored in a predetermined storage area in the volatile storage device 2B. Note that the Kanji index, the Yomi index, and the dictionary data part form a dictionary and exist for each different type of dictionary. The block indicates one of the areas divided for each capacity in which the character string in the dictionary can be searched most efficiently in the storage area of the dictionary data portion.

Here, the block will be described in more detail.
A block is a management unit of storage capacity that is physically or logically determined by the storage device and its driver and is statistically recommended to minimize the access time. In the present embodiment, each record in the dictionary is recorded in one block. Records are sequentially recorded in code order. If one record crosses a block boundary, that portion is recorded as unused and recorded from the beginning of the next block. These blocks have block numbers represented by consecutive integers. Further, in this embodiment, the search time can be shortened by limiting the block of the storage unit including the word by the reading index. If this is attempted by another method, if the search target word is not included in the dictionary, the entire dictionary will be searched, which will be very time consuming.

  The character recognition unit 32 has a function of recognizing a character string input by the input device 3. Specifically, the character recognition unit 32 recognizes handwritten characters based on a character recognition dictionary stored in the character recognition dictionary information storage unit 21 based on characters input by handwriting, and recognizes the recognized single or plural characters. Is displayed in the area of the recognized character result display window 42 on the screen of the display device 4 through the display processing unit 37.

  When the character string recognized by the character recognition unit 32 includes a character string “other than kana”, the search unit 33 corresponds to the character string “other than kana” from the kanji index. Search for a character string, further search block identification information corresponding to the searched character string from the Yomi index, and further, from among the blocks of the dictionary data portion specified by the searched block identification information The notation of the character string corresponding to the searched kana character string is searched, while the character string recognized by the character recognition unit 32 does not include the character string “other than kana”, and the kana character string is If it is included, the block identification information corresponding to the character string of the kana is searched from the Yomi index without using the Kanji index, and the searched block identification information A function of searching the representation of the character string corresponding to the character string of kana and the search from among the dictionary data of the block which is specified.

  Specifically, the search unit 33 determines whether or not “other than kana” is included in the character string before being determined as the input character from the recognition result of the handwritten input character by the character recognition unit 32, and based on the determination result In the form of predicting the character string following this character string, the character string following the character string including “kana predicting process” and “other than kana” that predicts the character string following the kana character string. It has a function of switching between certain “kanji prediction processing”. The search unit 33 has a function of searching various dictionaries in order to obtain the number of predictive conversion candidates that can be displayed in the candidate character display window 44. In order to obtain a prediction conversion candidate by the “kanji prediction process”, the search unit 33 searches the kanji index for various dictionaries, then searches the yomi index, and further searches the dictionary data unit. On the other hand, in order to obtain a predictive conversion candidate by the “kana prediction process”, the dictionary data part is searched after searching the reading index. That is, in the present embodiment, the reading index and the dictionary data portion used for the “kana prediction process” are also effectively used for the “kanji prediction process”. For this reason, there is no need to provide a dedicated Yomi index and dictionary data part for “Kanji prediction processing”, and only a kanji index with a data amount extremely smaller than that of the dictionary data part is added. By effectively using the area, it is possible to quickly output predictive conversion candidates regardless of whether the input character string includes “other than kana” or not.

  In addition, the search unit 33 performs a binary search on each character string arranged in the code order in each of the blocks of the kanji index, the yomi index, and the dictionary data unit, thereby determining the position where the desired data exists. It has the required function. As a result, the search speed can be further increased.

  The prediction candidate output unit 34 has a function of displaying the prediction conversion candidate obtained by the kana prediction process or the kanji prediction process on the candidate character display window 44 on the screen of the display device 4 through the display processing unit 37.

  The display order processing unit 35 is a function for setting the display order of prediction conversion candidates stored in the prediction candidate information storage unit 26.

  The dictionary editing unit 36 is a function for editing the learning dictionary stored in the learning dictionary information storage unit 24.

  The display processing unit 37 has a function of displaying various information, for example, displaying a character string searched by the search unit 33 as a candidate on the screen of the display device 4.

  The character recognition dictionary information storage unit 21 stores a character recognition dictionary for recognizing handwritten characters. This character recognition dictionary has information indicating a correspondence between a two-dimensional pattern and a character.

  The basic dictionary information storage unit 22 stores a dictionary data unit that is a main body of the basic dictionary. The dictionary data portion of this basic dictionary includes a kana character string as the first column of data, and the second column of data includes characters other than kana corresponding to the kana character string of the first column of data. It is provided with a string (for example, a string of characters including “Kana” and “Kana”, or a string of “Other than Kana” only), and stored in a form divided into a plurality of blocks in the arrangement direction of the code order. Has been. With this structure, a kana character string can be converted into a character string including “other than kana”. In particular, in the dictionary data portion of this basic dictionary, the kana character string that is the data in the first column is a kana character string that includes all the readings of the character string that includes “other than kana” that is the data in the second column. It has become.

  The prediction dictionary information storage unit 23 stores a dictionary data portion that is a main body of the prediction dictionary. The dictionary data portion of the prediction dictionary has the same structure as the dictionary data portion of the basic dictionary described above. However, in the dictionary data portion of the prediction dictionary, the kana character string that is the data in the first column is a part of the front of the reading of the character string that includes “other than kana” that is the data in the second column (for example, It is a kana character string that is abbreviated as the reading when reading the back of the character string. The kana character string in this case consists of, for example, 1 to 3 characters.

  The learning dictionary information storage unit 24 stores a dictionary data part serving as a main body of the learning dictionary. The dictionary data part of this learning dictionary has the same structure as the dictionary data part of each dictionary described above. However, the dictionary data portion of the learning dictionary includes a first learning dictionary data portion for converting a kana character string into a character string including “other than kana”, and a character string including “other than kana”. It is composed of a second learning dictionary data part for converting into a column. The dictionary data part of the learning dictionary also includes information indicating the frequency of input by the user for each character string.

  Further, a user dictionary information storage unit (not shown) stores a dictionary data unit that is a main body of the user dictionary. The dictionary data part of this user dictionary has the same structure as the dictionary data part of the basic dictionary, prediction dictionary, or learning dictionary described above. However, the dictionary data portion of this user dictionary allows the user to arbitrarily register the data in the first column and the data in the second column (for example, written as Yomi).

  In addition, a DL dictionary information storage unit (not shown) stores a dictionary data unit serving as a main body of a download dictionary (hereinafter referred to as “DL dictionary”). The dictionary data portion of the DL dictionary has the same structure as the dictionary data portion of each dictionary described above. In particular, the DL dictionary can be downloaded from the I / O device 5 through the network. The DL dictionary is provided to the user via the network by the dictionary, the provider of the character string prediction program, or the manufacturer of the information processing apparatus.

  The index information storage unit 25 stores a Chinese character index and a Yomi index. The kanji index includes a character string up to the first two characters of the data (kana character string) in the first column of the dictionary data portion (however, three or more characters are possible) as the second column data. As data, the first character of the data in the second column (character string including other than kana) corresponding to the data in the first column of the dictionary data portion is provided. That is, the kanji index is composed of data collected from the dictionary data part. The Yomi index has block identification information that designates a block of the dictionary data portion as the data in the second column, and the data in the first column of the block as the first column data and the first record in the code order It has data (kana character string).

  The prediction candidate information storage unit 26 stores information to be displayed as a prediction conversion candidate.

  Here, referring to FIG. 2 to FIG. 4, examples of operations such as predictive conversion on the screen of the display device 4 when “Kanji”, “Hiragana”, and “Kanji and Hiragana” are input by handwriting, respectively. Will be described.

  Note that an automatic selection mode and a manual selection mode are prepared as methods for selecting recognized character candidates that are recognition results of characters displayed on the screen of the display device 4. The mode can be freely selected by the user from a setting menu displayed on the screen. In the automatic selection mode, when the pen leaves the panel, the highest recognition character candidate is automatically selected, and the corresponding prediction candidate is displayed. On the other hand, in the manual selection mode, when the pen leaves the panel, the recognized character candidates are displayed, and the user selects the candidate and the corresponding prediction candidate is displayed.

  FIG. 2 is a diagram illustrating an example of operations such as predictive conversion on the screen of the display device 4 when “Kanji” is input by handwriting.

  First, as shown in FIG. 2A, when a screen is displayed on the display device 4 and handwriting input is started by pen touch in the handwritten character input window 41 at the lower right of the screen, character recognition is performed. According to the engine, the input trajectory is checked, and the input character is compared with the character pattern stored in the character recognition engine and stored in the character recognition dictionary information storage unit 21 until the touch pen leaves the handwritten character input window 41 of the display device 4. The recognition result of the character input by handwriting is searched single or plural from the dictionary. The character recognition engine may be any generally used in the art.

  In the automatic selection mode of the present embodiment, as shown in FIG. 2A, when a “large” Chinese character is input by pen touch into the handwritten character input window 41, it is displayed at the lower left of the screen of the display device 4. The recognition result of the handwritten character is displayed in a certain recognized character result display window 42, and the character display engine 43 is the closest to the input character in the character display window 43 at the top of the screen of the display device 4. The wax character is displayed as shown in FIG. 2 (b), and the prediction conversion is performed in the candidate character display window 44 at the center of the screen of the display device 4 by the kanji prediction process for the provisionally recognized recognition character “large”. The candidate character strings “Osaka”, “Large”, “Adult”, and “Significant” are displayed. Next, when “Osaka” is selected by the user from the character strings of the predictive conversion candidates, as shown in FIG. 2C, the character strings “fu”, “prefecture”, and “station” of the cooperative predictive conversion candidates are displayed. Etc. are displayed.

  FIG. 3 is a diagram illustrating an example of operations such as predictive conversion on the screen of the display device when “Hiragana” is input by handwriting.

  First, as shown in FIG. 3A, when “o”, which is one handwritten character, is input by pen touch into the handwritten character input window 41, next, as shown in FIG. 3B. In addition, when a character is automatically selected or manually selected from among the candidate characters that are the recognition results, and the selected character is set to the temporarily confirmed recognition character “O”, the center of the screen of the display device 4 is obtained by kana prediction processing. In the candidate character display window 44, the character strings “Thank you” and “Thank you” are displayed.

  FIG. 4 is a diagram illustrating an example of operations such as predictive conversion on the screen of the display device 4 when “kanji and hiragana” are input by handwriting.

  In FIG. 4A, as in FIGS. 2A and 2B, a candidate for a predictive conversion candidate for the tentative fixed character “Large” after the Chinese character “Large” is input in the handwritten character input window 41 is displayed. When it is displayed in the character display window 44 and then “ki” is input by handwriting in the handwritten character input window 41 as shown in FIG. 4B, FIG. As shown in FIG. 4D, when a predicted conversion candidate for the “large” provisionally confirmed character is displayed in the character display window 43 and “i” is selected from the candidates, In addition, in the candidate character display window 44, the character strings “.”, “?”, “!”, “Nani”, “So” are displayed for the cooperative prediction conversion candidate for the provisionally confirmed character “large”.

  Here, an example of a search operation performed by the search unit 33 will be described with reference to FIG.

  The search unit 33 uses various dictionaries in the search process, but here, only the process using the prediction dictionary will be described. The prediction dictionary is composed of a prediction dictionary kanji index, a prediction dictionary reading index, and a prediction dictionary data section. These three pieces of information have a character string (A) as the first column of data and a character string (B) as the second column of data. The character string (A) is data used for collation with a character string serving as a search key, and the character string (B) is data to be output as a search result.

  First, the search unit 33 performs kanji prediction determination as to whether or not a character other than kana is included in the conversion target character.

  As a result of the determination, if a character other than kana is included, kanji prediction processing is performed.

  In the kanji prediction process, for example, when the kanji “yama” is included, the search unit 33 performs a binary search from the character string (A) that is the first column data of the kanji index for prediction dictionary. The position where the “mountain” exists is obtained, and the character strings “Sun”, “Ya” and “Yama” corresponding to this “mountain” are extracted from the character string (B) which is the second column data.

  Next, the search unit 33 includes kana character strings “Sun”, “Ya”, and “Yama” by binary search from the character string (A) that is the first column data of the prediction dictionary reading index. Each position is obtained, and the block number corresponding to each position is extracted from the character string (B) that is the data in the second column. For example, “San” is located between “Sama” and “Sanka” in the character code order among the individual Kana character strings in the character string (A), and therefore, the block number 94 corresponding to “Sama”. Are extracted from the character string (B) which is the data in the second column. Further, since the kana character string “sanka” includes “san”, the block number 95 corresponding to “sanka” is also extracted from the character string (B) that is the data in the second column. Note that “The” is a character code lower than “Sun”, and “The” does not include “Sun” and thus is not extracted.

  Subsequently, the search unit 33 searches for the position of the character string including the kana character string “sun” by binary search from the character string (A) which is the first column data in the block with the block number 94 in the dictionary data part. The position of the character string including the kana character string “Sun” is obtained by binary search from the character string (A) which is the data in the first column in the block with the block number 95 in the dictionary data portion. A character string including “mountain” is extracted from the character string (B), which is the data in the second column, with the notation corresponding to each. For example, among the individual kana character strings in the character string (A) of the prediction data portion, “San” is a character string including “San”, and the character string (B) corresponding to “San” is Since “Mountain” is included, “San-in” is extracted, and this “San-in” is output as one of the prediction conversion candidates of “Mountain”.

  In addition, a prediction conversion candidate of “mountain” is output from other blocks of the dictionary data portion (not shown) and dictionary data portion blocks in various dictionaries other than the prediction dictionary by the same method.

  On the other hand, if the result of the determination does not include anything other than kana, kana prediction processing is performed.

  For example, when “Sun” is included, the search unit 33 includes the kana character string “Sun” by binary search from the character string (A) that is the first column data of the prediction dictionary reading index. Each corresponding position is obtained, the corresponding block number is extracted from the character string (B) that is the data in the second column, and then the character string (the data in the first column in the corresponding block in the dictionary data portion) A) The position where the kana character string “Sun” exists is obtained by binary search, and the corresponding notation is extracted from the character string (B) which is the data of the second column, and “Sun” predictive conversion is performed. Output as one of the candidates.

  With such a mechanism, it is possible to search faster than searching the entire dictionary.

  Next, with reference to FIG. 6 to FIG. 10, details of the data structure of the kanji index, the yomi index, and the dictionary data portion of various dictionaries will be described.

  The kanji index, the yomi index, and the dictionary data portion of various dictionaries are commonly used as a character string (A) as data in the first column, a character string (B) as data in the second column, and data from the third column onwards. Each attribute is provided. There are three types of attributes: attribute (1), attribute (2), and attribute (3). In addition, the kanji index for each dictionary and each dictionary does not include overlapping information in which the first and second character strings are the same.

  By sharing the data structure in this way, a limited storage area can be used effectively without waste, and the search speed can be improved.

FIG. 6 is a diagram illustrating an example of a data structure of a dictionary data portion of various dictionaries stored in the information processing apparatus according to the embodiment in a table format.
The dictionary data portion of the basic dictionary shown in the example of FIG. 6A is stored in the basic dictionary information storage unit 22 as described above, and the character string (A) is a kana character string (..., sasanka, ... , Sanka, ..., Sankaku, ...), and a character string (..., Sanchahana, ..., Participation, ..., △, ...) containing "other than kana" indicating the notation as a character string (B) It is stored in a form divided into blocks. Also, information (..., common noun, ..., common noun, ..., common noun, ...) indicating the part of speech as attribute (1) and priority (priority of display order of prediction conversion candidates) as attribute (2). (..., low priority, ..., normal, ..., normal, ...).

  The dictionary data portion of the prediction dictionary shown in the example of FIG. 6B is stored in the prediction dictionary information storage unit 23 as described above, and the kana character string (... , ..., Sany, ...), and a character string (..., triangle, III, etc., Sanin, ...) including "other than kana" indicating notation as a character string (B), and in a plurality of blocks It is stored in a segmented form. Also, information indicating the part of speech as the attribute (1) (..., common noun, common noun, ..., proper noun, ...) and information indicating the priority (priority of the display order of the prediction conversion candidates) as the attribute (2) (..., normal, low priority, ..., normal, ...).

  In the example shown in FIG. 6B, the character string “San” corresponding to the notation “triangle” is omitted, and the character string “Sanyo” corresponding to the notation “Sanyo Shinkansen” is omitted. In other words, when “san” is input by handwriting input, “triangle” is displayed as a predictive conversion candidate without inputting the subsequent character, and when “sanyo” is input by handwriting input, Even if the character following is not input, “Sanyo Shinkansen” is displayed as a predictive conversion candidate.

  The dictionary data portion of the learning dictionary shown in the example of FIG. 6C is stored in the learning dictionary information storage unit 24 as described above, and the kana character string (... , Ya, ...), and a character string (..., Yamasan, ..., along the Yamanote line, ...) that includes "other than kana" indicating the notation as a character string (B), and is divided into a plurality of blocks Stored in the form. Although not shown, the dictionary data portion of the learning dictionary includes a character string including “other than kana” as the character string (A) and a character string including the kana character string as the character string (B). There is also information. Moreover, the information (..., 5, ..., 2, ...) indicating the frequency is provided as the attribute (3).

  As shown in the example of FIG. 6C, the combinations of the character string (A) and the character string (B) are arranged in descending order of the frequency of input character determination by kana-kanji conversion. In addition, you may make it employ | adopt a priority instead of employ | adopting frequency. Moreover, the arrangement | sequence of the combination mentioned above is good also as an arrangement | sequence which displays the character confirmed as last input, ie, the last input character, on the uppermost part.

  The dictionary data portion of the user dictionary shown in the example of FIG. 6D is stored in a user dictionary information storage portion (not shown) as described above, and a kana character string (..., a, ...) and a character string (..., Sanyo Shinkansen, ...) including "other than kana" indicating notation as a character string (B), and stored in a form divided into a plurality of blocks. Also, information (..., common noun, ...) indicating the part of speech as the attribute (1), information (..., normal, ...) indicating the priority (priority of the display order of the prediction conversion candidates) as the attribute (2), and It has. The character string (A) “A” and the character string (B) “Sanyo Shinkansen” are arbitrarily registered by the user.

  The dictionary data portion of the DL dictionary shown in the example of FIG. 6 (e) is stored in a DL dictionary information storage portion (not shown) as described above. For example, a dialect dictionary such as “Kansai dialect dictionary” or “medical terminology” There are specialized dictionaries such as “Dictionary”.

  The DL dictionary includes a kana character string (..., Sankakuko, ...) as a character string (A), and a character string (..., △ lake, ...) including "other than kana" indicating notation as the character string (B). And is stored in a form divided into a plurality of blocks. Also, information (..., proper noun, ...) indicating the part of speech as the attribute (1), information (..., normal, ...) indicating the priority (priority of the display order of the prediction conversion candidates) as the attribute (2), and It has. This DL dictionary is downloaded by the user.

  In addition, the storage device 2A includes a cooperative prediction dictionary (not shown). This cooperative prediction dictionary includes, for example, a fixed notation that is a notation selected as a predictive conversion candidate, a collocation / associative notation that is a notation connected to the fixed notation, a character string (yomi character string) indicating reading, a part of speech, , Information associated with priority. The definite notation and the combined word / associative notation in this cooperative prediction dictionary include “characters other than kana”. On the other hand, the Yomi character string in the cooperative prediction dictionary is a kana character.

FIG. 7 is a diagram illustrating a configuration example of the kanji index stored in the information processing apparatus according to the embodiment in a table format.
The kanji index for basic dictionary shown in the example of FIG. 7A is stored in the index information storage unit 25 as described above, and a character string (..., mountain including “other than kana” as the character string (A). , Mountain, mountain, mountain,..., And a kana character string (..., Saza, Zan, Yama, Wasa,...) As a character string (B).

  The kanji index for prediction dictionary shown in the example of FIG. 7B is stored in the index information storage unit 25 as described above, and a character string (..., mountain including “other than kana” as the character string (A). , Mountain, mountain,..., And a character string (..., San, Ya, Wa,...) As a character string (B).

  In the example of FIGS. 7A and 7B, the character string (B) is a character string up to the first two characters of the character string of the character string (A) in the block of the dictionary data portion. However, it is possible to make it 3 or more characters without being limited to 2 characters in front. These kanji indexes are constructed in advance based on the correspondence between the Yomi character strings and the notations in the dictionary data portions of the basic dictionary and the prediction dictionary described above, and the arrangement of the character strings (A) is in the character code order. However, other code orders are possible without being limited to the character code order.

  FIG. 8 is a diagram illustrating an example of a candidate character display window 44 by the information processing apparatus according to the embodiment. The character strings are displayed in order from the upper character string in FIG.

  In this display example, the display order of “Yamasan” is higher, and the display order of “Yamachahana” is lower. This "Sancha Hana" was searched from the basic dictionary prediction dictionary before "Yamanokai" and "Yamaki", but the priority associated with the basic dictionary prediction dictionary of the search source is "low priority" This indicates that the display order is lower than “Yamanokai” or “Yamaki” by the processing of the display order processing unit 35.

Next, a detailed example of this embodiment will be described. In this detailed example, the prediction dictionary and the basic dictionary are composed of a Kanji index, a Yomi index, and a data part.
FIG. 9 is a diagram showing details of the prediction dictionary stored in the information processing apparatus according to the embodiment of the present invention in a tabular format.
The prediction dictionary in this detailed example includes a prediction dictionary kanji index, a prediction dictionary reading index, and a prediction dictionary data section, as described with reference to FIG.
The kanji index for prediction dictionary shown in the example of FIG. 9A is stored in the index information storage unit 25, and is a character string (..., mountain, mountain, etc.) including "other than kana" as the character string (A). And a character string (..., Sun, Yama, Yama ...) as a character string (B).

  The prediction dictionary reading index shown in the example of FIG. 9B is stored in the index information storage unit 25, and is a kana character string (..., Summer, sangka, the...) As the character string (A). And a block number (..., 94, 95, 96,...) That designates a block of the dictionary data portion of the prediction dictionary as a character string (B). In the character string (A), a kana character string positioned at the head of the block designated by the block number of the character string (B) is arranged in the order of codes.

  The block of the prediction dictionary data part of the block number 94 shown in the example of FIG. 9C is stored in the prediction dictionary information storage part 23, and the kana character string (summer,... ..., Sany, ...), and a character string (various, ..., ..., Sanin, ...) including "other than kana" as the character string (B).

  The block of the prediction dictionary data part of block number 95 shown in the example of FIG. 9 (d) is stored in the prediction dictionary information storage part 23, and a kana character string (sanka,... ...) and a character string (participation, ..., ...) including "other than kana" as the character string (B).

  The usage of the prediction dictionary shown in FIG. 9 is as described in the example of FIG.

  According to the configuration of FIG. 9, the search processing function using the prediction dictionary is improved and the search range of prediction conversion candidates can be narrowed, so that the processing load on the prediction conversion process can be reduced.

FIG. 10 is a diagram showing a detailed example of the basic dictionary stored in the information processing apparatus according to the embodiment of the present invention in a table format.
The basic dictionary in this detailed example is composed of a basic dictionary kanji index, a basic dictionary reading index, and a basic dictionary data section as described with reference to FIG.
The kanji index for basic dictionary shown in the example of FIG. 10 (a) is stored in the index information storage unit 25, and a character string (..., mountain, mountain, etc.) including "other than kana" as the character string (A). Mountain, mountain, mountain, mountain,..., And a character string (..., Saza, Sun, Zan, Yaki, Yama, Wasa,...) As a character string (B).

  The basic dictionary reading index shown in the example of FIG. 10B is stored in the index information storage unit 25, and is a kana character string (..., Sage, fillet, sagittal,...) As a character string (A). And a block number (..., 401, 402, 403,...) That designates a block of the dictionary data portion of the basic dictionary as a character string (B). In the character string (A), a kana character string positioned at the head of the block designated by the block number of the character string (B) is arranged in the order of codes.

  The block of the basic dictionary data portion with the block number 401 shown in the example of FIG. 10C is stored in the basic dictionary information storage portion 22 and is a kana character string (sage,... ...) and a character string (lower, ..., ...) including "other than kana" as the character string (B).

  The block of the basic dictionary data part with the block number 402 shown in the example of FIG. 10D is stored in the basic dictionary information storage part 23, and the character string (A) is a kana character string (... ...) and a character string (..., Sanchahana ...) including "other than kana" as the character string (B).

  The usage of the basic dictionary shown in FIG. 10 is the same as in the example of FIG.

  Further, according to the configuration of FIG. 10, the search processing function by the basic dictionary is also improved and the search range of the prediction conversion candidates can be narrowed, so that the processing load for the prediction conversion processing can be reduced.

  Similarly to FIGS. 9 and 10, the learning dictionary, the user dictionary, and the DL dictionary are also provided with a kanji index and a Yomi index.

  As can be seen from the above description, the character strings (A) are arranged in code order, for example, but the character strings (B) are not arranged in code order.

  Further, when the plurality of candidates to be displayed correspond to the same character string as shown in the character string (A) in FIG. 7, for example, the display order may be any order. For example, the registration order of words may be used, or the order of character strings (B) may be used. Or you may adjust arbitrarily considering the order output as a candidate.

Next, the operation | movement of the prediction conversion process by the information processing apparatus which concerns on this embodiment is demonstrated.
FIG. 11 is a flowchart illustrating an example of operations related to prediction conversion candidate display by the information processing apparatus according to the embodiment.
First, when a character is input by a predetermined operation on the input device 3 in the same manner as in FIGS. 2A and 3A (step S1), the character recognition unit 32 causes the input character and character to be input. By collating with a dictionary stored in the recognition dictionary information storage unit 21, a single or a plurality of characters as a recognition result of the handwritten input character are searched from the dictionary, and the search result is displayed through the display processing unit 37. It is displayed in the recognized character result display window 42 at the lower left of the screen of the device 4 (step S2).

  The character recognition unit 32 uses the search result closest to the handwritten input character among the character search results of the recognition result of the handwritten input character as a provisionally confirmed recognition character, and displays a recognized character result display window through the display processing unit 37. It is displayed on the upper left in 42. For example, when the displayed temporarily confirmed recognition character does not match the character intended by the user (NO in step S3), the user temporarily recognizes the recognition result among the recognition result characters in the recognized character result display window 42. If, for example, a character intended by itself is selected from other than a character by pen touching the display portion of the character, the selected character is displayed in the character display window 43 on the screen as a new tentatively recognized character (step) S4). At this stage, the displayed character is not confirmed as an input character. In this state, by touching the part where the “Enter key” displayed on the screen is displayed, the character that has not been confirmed is displayed. The column is confirmed as the entered character string.

  In the above-described unconfirmed state, when it is desired to input a character that follows the tentatively recognized character, it is only necessary to input one character by handwriting by pen touching the handwritten character input window 41 on the input screen again.

  When the process of step S4 is performed, or because the temporarily confirmed recognized character displayed in the recognized character result display window 42 matches the character intended by the user (YES in step S3), step S4 If the above process is not performed, the search unit 33 determines whether or not the character string “other than kana” is included in the temporarily confirmed character string (step S5).

  As a result of the determination, if the character string includes a character other than “kana” (YES in step S5), kanji prediction processing is performed (step S6), and the character string includes a character other than “kana”. If not (NO in step S5), kana prediction processing is performed (step S7).

Here, the kana prediction process in step S7 will be described.
FIG. 12 is a flowchart illustrating an example of an operation related to the display of the prediction conversion candidate by the kana prediction process of the information processing apparatus according to the embodiment.
In this kana prediction process, the search unit 33 searches the learning dictionary (step S21), searches the user dictionary (step S22), searches the DL dictionary (step S23), searches the prediction dictionary (steps S24 to S27), and The basic dictionary search (step S28) is executed in this order. The plurality of steps constituting the search step of each dictionary are the same. Here, the details of the processes in steps S24 to S27 will be described focusing on the search of the prediction dictionary.

  When the retrieval unit 33 calls the prediction dictionary (step S24), the retrieval unit 33 retrieves the prediction dictionary reading index included in the prediction dictionary (step S25), and the character that is data in the first column of the prediction dictionary reading index. Each position where the target kana character string exists is obtained from the column (A) by binary search, and the corresponding block number is extracted from the character string (B) which is the data of the second column.

  Subsequently, the search unit 33 searches for a block of the dictionary data portion respectively designated by the extracted block number (step S26), and performs a binary search from the character string (A) that is the first column data in the block. To obtain the position of the character string including the target kana character string, extract the corresponding notation from the character string (B) which is the data in the second column, and store them in a predetermined storage area as a predictive conversion candidate Store (step S27). These steps are repeated while the character string (A) of the reading index matches the target kana character string.

  The processes in steps S24 to S27 are the same in the search of the learning dictionary (step S21), the search of the user dictionary (step S22), the search of the DL dictionary (step S23), and the search of the basic dictionary (step S28). It becomes.

  Next, the display order processing unit 35 refers to the priority information and the part of speech information in the dictionary of the search source for the information of the prediction conversion candidate stored in the prediction candidate information storage unit 26, and classifies the part of the priority information and the part of speech information. Recognize a predetermined priority level corresponding to the type of part of speech indicated by (2), set the display order of predictive conversion candidates (step S29), and display the predictive conversion candidates on the screen of the display device 4 in the set order ( Step S30). When a candidate is selected by one user from the prediction conversion candidates displayed on the screen of the display device 4 (step S31), and the confirmation input of the prediction result to the selected candidate is made (step S32), The selected candidate is displayed in the character display window 44 on the screen.

  In this embodiment, the display order of prediction conversion candidates searched from the learning dictionary is higher than the display order of prediction conversion candidates searched from other dictionaries even after the processing by the display order processing unit 35, and is searched from the prediction dictionary. It is assumed that the display order of the predicted conversion candidates is higher than the display order of the predicted conversion candidates searched from the basic dictionary even after the processing by the display order processing unit 35 (step S7).

  As a method for setting the priority order for each part of speech, a method for setting a priority order for various parts of speech by a user and setting by the user, a method for setting a part of speech priority according to the type of various input fields on the character input screen, and A method of analyzing the part-of-speech of the input character, storing the analysis result, selecting the part-of-speech that will be input next, and setting the selected part-of-speech preferentially as a predictive conversion candidate and setting it by grammar analysis processing Can be mentioned.

Here, the kanji prediction process in step S6 will be described.
FIG. 13 is a flowchart illustrating an example of operations related to display of prediction conversion candidates by the kanji prediction process of the information processing apparatus according to the embodiment.
In this kanji prediction process, the search unit 33 searches the learning dictionary (step S41), searches the user dictionary (step S42), searches the DL dictionary (step S43), searches the prediction dictionary (steps S44 to S48), and The basic dictionary search (step S49) is executed in this order. The plurality of steps constituting the search step of each dictionary are the same. Here, the details of the processes in steps S44 to S48 will be described focusing on the search of the prediction dictionary.

  When the retrieval unit 33 calls the prediction dictionary (step S44), the retrieval unit 33 retrieves the prediction dictionary kanji index included in the prediction dictionary (step S45), and the character that is data in the first column of the prediction dictionary kanji index. Each position where a character other than the target kana exists is obtained from the column (A) by binary search, and the corresponding kana character is extracted from the character string (B) which is data in the second column.

  Subsequently, the search unit 33 searches the prediction dictionary reading index included in the prediction dictionary (step S46), and from the character string (A) that is the first column data of the prediction dictionary reading index. Each position where the kana character string extracted by the binary search exists is obtained, and the corresponding block number is extracted from the character string (B) which is the data of the second column.

  Subsequently, the search unit 33 searches the blocks of the dictionary data part respectively designated by the extracted block numbers (step S47), and performs a binary search from the character string (A) that is the first column data in the block. To obtain the position of the character string including the target kana character string, extract the corresponding notation from the character string (B) which is the data in the second column, and store them in a predetermined storage area as a predictive conversion candidate Store (step S48).

These steps are repeated until the character string (A) of the kanji index matches the character string other than the target kana.

  The processing in steps S44 to S48 is the same in the learning dictionary search (step S41), the user dictionary search (step S42), the DL dictionary search (step S43), and the basic dictionary search (step S49). It becomes.

  Next, the display order processing unit 35 refers to the priority information and the part of speech information in the dictionary of the search source for the information of the prediction conversion candidate stored in the prediction candidate information storage unit 26, and classifies the part of the priority information and the part of speech information. Recognize a predetermined priority level corresponding to the type of part of speech indicated by (2), set the display order of prediction conversion candidates (step S50), and display the prediction conversion candidates on the screen of the display device 4 in the set order ( Step S51). When one candidate is selected from the prediction conversion candidates displayed on the screen of the display device 4 (step S52), and the confirmation result is input to the selected candidate (step S53), the selected candidate is selected. The candidates are displayed in the character display window 44 on the screen.

  Then, returning to FIG. 11, the dictionary editing unit 36 registers the selected result in the learning dictionary. If already registered, the frequency in the learning dictionary is updated (step S11). Then, the dictionary editing unit 36 stores information on the selected character on the learning dictionary in a predetermined storage area as history information used last time.

  The search unit 33 searches for the collocation / association notation that is a linked prediction conversion candidate by collating the confirmed notation of the linked prediction dictionary with the confirmed character string (step S12), and the predicted candidate output unit 34 The retrieved candidates are displayed on the display device 4 through the display processing unit 37 (step S13).

  When the user selects a desired candidate from among the displayed linked prediction candidates by a pen touch (step S14), the confirmed input of the linked prediction result to the selected candidate is made (step S14). In step S15, the selected candidate is displayed in the character display window 43 on the screen, and the selected candidate is displayed in the character display window 43 on the screen. The dictionary editing unit 36 updates the frequencies of the selected candidate search source dictionary and the learning dictionary (step S16). The dictionary editing unit 36 stores the information of the selected character on the learning dictionary in a predetermined storage area as history information used last time.

  If the handwritten input has not ended (NO in step S17), the process returns to step S1, and if the handwritten input has ended (YES in step S17), the series of processes ends.

  As described above, in the information processing apparatus according to the embodiment of the present invention, when a character string including “other than kana” is input by handwriting, the notation indicating the reading of the input character is searched from various kanji indexes, In response to the search results, and searches for various notations containing handwritten input characters other than “kana”, the dedicated dictionary is compared with the conventional configuration for displaying predictive conversion candidates. It is possible to perform predictive conversion processing and cooperative predictive conversion processing based on a character string including “other than kana” input by handwriting by effectively utilizing a basic dictionary and a prediction dictionary that have been conventionally used without the necessity of providing a new one. Therefore, the burden on the user input operation when inputting a character string including “other than kana” by handwriting can be greatly reduced without significantly increasing the storage capacity and processing load of the device.

  Therefore, as in the past, the same operation for predictive conversion when only Kana characters are input by hand can be realized even when a character string including “other than Kana” is input by hand, greatly improving operability. To do. Therefore, it is possible to greatly improve the efficiency of the predictive conversion function implementation based on the handwritten Kanji characters and the efficiency of the input work.

  In addition, the character string prediction performed by the key press input method is realized by the handwriting input method, and the processing speed equivalent to the character input prediction process by the key press input method is achieved without the need for providing a dedicated kanji prediction conversion dictionary. Can keep.

  In addition, by providing a kanji index for the prediction dictionary and the basic dictionary, the kanji index can be configured to be suitable for each dictionary. Compared with the case where the index information is used, unnecessary search can be suppressed, and search performance is improved.

  The present invention is not limited to the above-described embodiment as it is, and can be embodied by modifying the constituent elements without departing from the scope of the invention in the implementation stage. Various inventions can be formed by appropriately combining a plurality of constituent elements disclosed in the embodiment. For example, some components may be omitted from all the components shown in the embodiment. Furthermore, you may combine suitably the component covering different embodiment.

  In addition, the method described in the above embodiment is a program that can be executed by a computer, such as a semiconductor memory (flash memory, etc.), a magnetic disk (hard disk, floppy (registered trademark) disk, etc.), an optical disk (CD-ROM, DVD, etc.). Etc.) and can be distributed in a storage medium such as a magneto-optical disk (MO).

  In addition, as long as the storage medium can store a program and can be read by a computer, the storage format may be any form.

  In addition, an OS (operating system) running on a computer based on an instruction of a program installed in the computer from a storage medium, MW (middleware) such as database management software, network software, and the like realize the above-described embodiment. A part of each process may be executed.

  Further, the storage medium in the present invention is not limited to a medium independent of a computer, but also includes a storage medium in which a program transmitted via a LAN, the Internet, or the like is downloaded and stored or temporarily stored.

  Further, the number of storage media is not limited to one, and the case where the processing in the above embodiment is executed from a plurality of media is also included in the storage media in the present invention, and the media configuration may be any configuration.

  The computer according to the present invention executes each process in the above-described embodiment based on a program stored in a storage medium, and is a single device such as a personal computer or a system in which a plurality of devices are connected to a network. Any configuration may be used.

  In addition, the computer in the present invention is not limited to a portable information terminal, a mobile phone, a personal computer, and the like, and includes an arithmetic processing unit, a microcomputer, and the like included in home appliances, and the functions of the present invention can be realized by a program. It is a generic term for all possible equipment and devices.

  DESCRIPTION OF SYMBOLS 1 ... Control apparatus, 2A ... Nonvolatile memory | storage device, 2B ... Volatile memory | storage device, 3 ... Input device, 4 ... Display apparatus, 5 ... I / O device, 10 ... Bus, 21 ... Character recognition dictionary information storage part, 22 ... basic dictionary information storage unit, 23 ... prediction dictionary information storage unit, 24 ... learning dictionary information storage unit, 25 ... index information storage unit, 26 ... prediction candidate information storage unit, 31 ... storage processing unit, 32 ... character recognition unit, 33 ... Search unit, 34 ... Prediction candidate output unit, 35 ... Display order processing unit, 36 ... Dictionary editing unit, 37 ... Display processing unit.

Claims (3)

In a computer comprising an input device capable of inputting a handwritten character string, a storage medium for storing information, and a display device for displaying information on a screen,
1) including information that associates a character string representation other than kana with a kana character string indicating at least a part of reading or heading of the character string, the kana character strings are arranged in code order, and the information A dictionary data part that is divided into a plurality of blocks in the arrangement direction of the code order; and 2) at least a part of the character string and a character string other than the kana character string included in the dictionary data part. A first index that includes associated information and in which a character string other than the kana is arranged in code order; 3) block identification information that specifies a block of the dictionary data portion; and a head of a block that is specified by the identification information A second index in which the kana character strings are arranged in code order and stored in a predetermined storage area of the storage medium. And processing functions,
A recognition function for recognizing a character string input by the input device;
When a character string other than kana is included in the character string recognized by the recognition function, a kana character string corresponding to a character string other than the kana is searched from the first index, and A block identification information corresponding to the retrieved kana character string is retrieved from the second index, and the retrieved kana character is selected from the blocks of the dictionary data portion specified by the retrieved block identification information. If the character string corresponding to the column is searched for, and the character string recognized by the recognition function does not include a character string other than kana and includes a kana character string, The dictionary specified by the searched block identification information is searched for the block identification information corresponding to the kana character string from the second index without using the index of 1. A search function of searching the representation of the character string corresponding to the character string of kana and the search from the block over data portion,
A character string prediction program for realizing a display processing function for displaying on the screen of the display device as candidates a notation of a character string searched by the search function. The first index, the second index, and the dictionary data part exist for different types of dictionaries,
The character string prediction program according to claim 1, wherein the search function performs a search using the first index, the second index, and a dictionary data portion that exist for each dictionary. An input device capable of inputting a handwritten character string;
A storage medium for storing information;
A display device for displaying information on the screen;
1) including information that associates a character string representation other than kana with a kana character string indicating at least a part of reading or heading of the character string, the kana character strings are arranged in code order, and the information A dictionary data part that is divided into a plurality of blocks in the arrangement direction of the code order; and 2) at least a part of the character string and a character string other than the kana character string included in the dictionary data part. A first index including the associated information, in which the kana character string is arranged in code order, and 3) block identification information for designating a block of the dictionary data portion and at the head of the block designated by the identification information A storage process for storing, in a predetermined storage area of the storage medium, a second index in which the kana character string is arranged in code order, including information that associates the kana character string with the position And means,
Recognition means for recognizing a character string input by the input device;
When a character string other than kana is included in the character string recognized by the recognition means, a kana character string corresponding to a character string other than the kana is searched from the first index, and A block identification information corresponding to the retrieved kana character string is retrieved from the second index, and the retrieved kana character is selected from the blocks of the dictionary data portion specified by the retrieved block identification information. If the character string corresponding to the column is searched and the character string recognized by the recognizing means does not include a character string other than kana and includes a kana character string, The dictionary specified by the searched block identification information is searched for the block identification information corresponding to the kana character string from the second index without using the index of 1. Search means for searching the representation of the character string corresponding to the character string of kana and the search from the block over data portion,
An information processing apparatus comprising: a display processing unit configured to display on the screen of the display device as a candidate a notation of a character string searched by the search unit.

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