KR20110032470A - Apparatus and method for word game - Google Patents

Abstract

PURPOSE: An apparatus and a method for a word game are provided to enhance the degree of difficulty of a game by presenting a word having a difficult end letter. CONSTITUTION: An apparatus for a word game comprises: a word database(102); a user input portion(104) in which a presented word from a user is input; a word selecting unit(106) which extracts a word from the word database, creates a candidate word group, extracts the information on degree of difficulty from the word database, compares the degree of difficulty and literature frequency of the extracted words, and selects one word of the candidate word; and a word output unit(108) which displays the word selected from the word selecting unit.

Description

Apparatus and method for word game

The present invention relates to a game progress technology using an information terminal such as a computer.

A word ending game is a series of games in which one word is presented and another word begins with the last syllable of the word. Two or more words or one alternates with a computer or game machine. It can be done in a manner.

Since the end-game is a game that the opponent loses if the end does not present within a certain time, it is important to present a difficult word for the opponent to present the end to win the game. Therefore, even when the end game is implemented with a computer or a game machine, it is necessary to study a method of selecting a presenter so that it is difficult for a game performer to present the end to increase the difficulty of the game.

Embodiments of the present invention analyzes words that begin with the end of a new word to be presented in the ending game, and selects a word that is difficult to use because of less document frequency, fewer words that begin with the end, or a higher difficulty To provide a way to do this.

Word game apparatus according to an embodiment of the present invention for solving the above problems, a word database for storing a plurality of words, the document frequency of each word and the difficulty information of each word; A user input unit configured to receive a suggestion from a user; Words starting from the input syllables of the input word are extracted from the word database to generate candidate word groups, and for each of the candidate words included in the candidate word groups, the end syllables of each candidate word as starting syllables. A word selector which extracts document frequency and difficulty information of the word from the word database, and selects one word among the candidate words by comparing the document frequency and difficulty information of the extracted words; And a word output unit configured to display the word selected by the word selector to the user.

On the other hand, the word game apparatus according to another embodiment of the present invention, a word database for storing a plurality of words and the difficulty information of each word; A start frequency database in which the frequency of the first syllable of all words stored in the word database and the word database of words starting with the first syllable is stored; A user input unit configured to receive a suggestion from a user; Words starting from the input syllables of the input word are extracted from the word database to generate a candidate word group, and a word having the first syllable as the first syllable for each candidate word included in the candidate word group. Extracts the number of times from the start frequency database, extracts a difficulty level of the word having the first syllable as the first syllable from the word database, compares the extracted start frequency and the difficulty information, and then selects one of the candidate words. A word selector for selecting a word of the word; And a word output unit configured to display the word selected by the word selector to the user.

On the other hand, the word game apparatus according to another embodiment of the present invention, a word database for storing a plurality of words, the document frequency of each word and the difficulty information of each word; A start frequency database in which the frequency of the first syllable of all words stored in the word database and the word database of words starting with the first syllable is stored; A user input unit configured to receive a suggestion from a user; Words starting from the input syllables of the input word are extracted from the word database to generate candidate word groups, and for each of the candidate words included in the candidate word groups, the end syllables of each candidate word as starting syllables. Extracts document frequency and difficulty information from the word database, extracts the number of words having the first syllable as the first syllable of each candidate word from each of the candidate words included in the candidate word group, from the starting frequency database, A word selector which selects one word among the candidate words by comparing document frequency, difficulty information, and start frequency information of the extracted words; And a word output unit which displays the word selected by the word selector to the user. It includes.

On the other hand, the word game method in a word game apparatus according to an embodiment of the present invention, the word game device, the step of receiving a presentation from the user; Generating, at the word game apparatus, candidate word groups by extracting words beginning with an end syllable of the inputted present word from the word database; Extracting, from the word database, document frequency and difficulty information of a word having an end syllable as a starting syllable for each candidate word included in the candidate word group in the word game device; In the word game device, selecting one word of the candidate words by comparing the extracted document frequency and difficulty information; And outputting the selected word in the word game device.

On the other hand, the word game method in a word game apparatus according to another embodiment of the present invention, the word game device, the step of receiving a presentation from the user; Generating, at the word game apparatus, candidate word groups by extracting words beginning with an end syllable of the inputted present word from the word database; Extracting, in the word game apparatus, a frequency (starting frequency) from the word database of a word having the first syllable as the first syllable of each candidate word for each of the candidate words included in the candidate word group; Extracting, from the word database, a difficulty level of a word having the first syllable as the first syllable in the word game device; In the word game device, selecting one word of the candidate words by comparing the starting frequency and difficulty information; And outputting the selected word in the word game device.

On the other hand, the word game method in a word game device according to another embodiment of the present invention, the word game device, the step of receiving a presentation from the user; Generating, at the word game apparatus, candidate word groups by extracting words beginning with an end syllable of the inputted present word from the word database; Extracting, from the word database, document frequency and difficulty information of a word having an end syllable as a starting syllable for each candidate word included in the candidate word group in the word game device; Extracting, in the word game apparatus, a frequency (starting frequency) from the word database of a word having the first syllable as the first syllable of each candidate word for each of the candidate words included in the candidate word group; In the word game device, selecting one word among the candidate words by comparing the extracted document frequency, difficulty information, and starting frequency; And outputting the selected word in the word game device.

Embodiments of the present invention analyze words that begin with the end of a new word to be presented in a word game, such as a ending game, less frequently used because of less document frequency, fewer words starting with the end, or higher difficulty By selecting a difficult word, the user can increase the difficulty of the game by presenting a word that is difficult to present the end.

Hereinafter, specific embodiments of the present invention will be described with reference to the drawings. However, this is only an example and the present invention is not limited thereto.

In describing the present invention, when it is determined that the detailed description of the known technology related to the present invention may unnecessarily obscure the subject matter of the present invention, the detailed description thereof will be omitted. The following terms are defined in consideration of the functions of the present invention, and may be changed according to the intention or custom of the user, the operator, and the like. Therefore, the definition should be based on the contents throughout this specification.

The technical spirit of the present invention is determined by the claims, and the following embodiments are merely means for efficiently explaining the technical spirit of the present invention to those skilled in the art.

1 is a diagram showing a word game device 100 according to an embodiment of the present invention.

As illustrated, the word game apparatus 100 according to an embodiment of the present invention includes a word database 102, a user input unit 104, a word selector 106, and a word output unit 108. do.

The word database 102 is a database in which a plurality of words, document frequency of each word, and difficulty information of each word are stored. The word database 102 may be configured, for example, as shown in Table 1 below.

word Document frequency difficulty bag 70 0.1 Go 82 0.1 Vacation 61 0.2 life 43 0.2 bottled water 40 0.4 life 37 0.6 religion 11 0.9 Termination 9 0.9 student 37 0.1 School bell 12 0.2

Table 1 shows an example of the word database 102 composed of Korean words, but is not limited to a specific language and the like, and words of any language such as English and Japanese may be used.

Among the items in Table 1, "document frequency" is a value representing the frequency of use of the word in literature (Internet documents or books, etc.). For example, the literature frequency of "bag" in the table is 70, the literature frequency of "termination" is 9, which means that "bag" has been used 70 times in this document and nine times for "termination". The document for calculating the document frequency may be any document, but since the document frequency is for comparing the frequency of use of each word with each other, the document frequency for each word should be calculated from the same document.

On the other hand, in Table 1, "difficulty" is a value representing the degree of difficulty of each word is displayed as a real number between 0 and 1. For example, in Table 1, the difficulty of "Ko" is 0.1, the difficulty of "Religion" is 0.9, indicating that "Religion" is a more difficult word than "Ko".

There may be various methods of determining the difficulty, but only a few are described as follows.

First, you can use the number of letters in the word. That is, the longer the word is, the more likely it is to be a difficult and complex word, so that the longer the word is, the higher the difficulty is. In this case, the difficulty level of each word may be calculated as "length of word ÷ length of longest word".

Next, ontology is used. Words stored in the word database 102 may be connected in an “isA” relationship according to their semantic relationship, and thus an ontology may be constructed using the words stored in the word database 102. In this case, the higher the level in the ontology, the higher the level or the difficulty of the word, so when using the ontology, the difficulty of each word can be calculated as "level of words ÷ maximum level of the ontology".

The difficulty may also be determined according to the difficulty of the literature in which the word is used. For example, there are n documents and the difficulty of each document is (D ₁ , D ₂ , D ₃ , ..., D _n ) _where D _n is a real number between 0 and 1 If the frequency of a particular word A appearing in (F ₁ , F ₂ , F ₃ , ..., F _n ) (that is, the word A appears F _k times in the literature of difficulty D _k ), Difficulty of the word A can be calculated by the following equation (1).

The above equation may be used to express the relative difficulty between words. The more difficulty a word appears in a document with high difficulty, the higher the difficulty, and the more difficulty a word appears in a document with low difficulty. For example, if the document is a textbook, the difficulty level can be determined by sequentially assigning the document level from 0 to 1 from the first grade textbook to the high school textbook and calculating the frequency of use in the textbooks for each word. have.

Next, the user input unit 104 receives a suggestion from the user. The predicate may be any word when the game is first started, and may be a word that begins with the end syllable of the output word after the word is output by the word output unit 108. To determine whether a word input from the user input unit 104 corresponds to a word in a dictionary rather than any word, or to determine whether the word starts with the end syllable of the word output from the word output unit 108. For example, the word game apparatus 100 may include a separate determination module (not shown), wherein the determination module is not a word stored in the word database 102 or a word inputted from the user input unit 104. If it is not a word that begins with the end syllable of the output word (ie, violates the rules of the end-game game), it may be configured to output that the user has lost and to end the game.

Next, the word selector 106 selects one of the words starting with the end syllable of the word (suggested word) input from the user input unit 104 from the word database 102. In detail, the word selector 106 extracts words starting from the end syllable of the predicate input from the user input unit 104 in the word database 102 to generate a candidate word group, and the candidate included in the candidate word group. For each of the words, the document frequency and difficulty information of a word having the end syllable of each candidate word as a starting syllable are extracted from the word database 102, and the document frequency and difficulty information of the extracted words are compared to compare the information among the candidate words. You choose one word. A detailed word selection process in the word selector 106 will be described in detail with reference to FIG. 2.

Finally, the word output unit 108 displays the word selected by the word selector 106 to the user. To this end, the word output unit 108 may include an output device such as an LCD monitor or a speaker.

2 is a flowchart illustrating a word selection method 200 of the word game apparatus 100 according to an exemplary embodiment.

First, when the user input unit 104 receives a suggestion from the user (202), the word selector 106 extracts words starting with the end syllable of the inputted present word from the word database to generate a candidate word group (204). ).

For example, when the presentation received by the user input unit 104 is "vacation", the end syllable is "hak". In the word database 102 illustrated in Table 1, the words "study" as the first syllable are "student" and "school class", so the two words are candidate word groups that can be presented as the end of the present word.

Next, for each of the candidate words included in the candidate word group, the document frequency and difficulty information of the word having the end syllable of each candidate word as the starting syllable is extracted from the word database 102 (206).

In the above example, the end syllable of "student" among the candidate words is "live", and the words starting with "live" in the word database 102 are "life", "living water", and "life". In addition, the end syllable of the candidate word "school bell" is "bell", and the words starting with "bell" in the word database 102 are "religion" and "termination". Therefore, in this step, the document frequency and difficulty information for each of the five words is extracted from the word database 102.

Next, one of the candidate words is selected by comparing the extracted document frequency and difficulty information.

In more detail, first, the sum, average, standard deviation, and maximum value of the document frequencies of words having starting syllables as the end syllables of each candidate word are calculated for each candidate word (208).

In the above example, the word frequency starting with the end syllable of "student" among the candidate words, that is, the document frequency of "life", "living water" and "life" is 43, 40 and 37, respectively, so that their sum, mean and standard deviation And the maximum values are 120, 40, 2.45, and 43, respectively.

Also, among the candidate words, the words starting with the end syllable of the "school bell", that is, the "religion" and the "end", are 11 and 9, respectively, so the sum, mean, standard deviation, and maximum are 20, 10, and 1, respectively. , 11

Next, using the sum, mean, standard deviation, and maximum value of the document frequencies calculated for each candidate word, the average is above a certain value (X), the standard deviation is above a certain value (Y), or the maximum value. If the predetermined value Z or more, the corresponding candidate word is excluded from the candidate word group (210). At this time, each of these may be applied alone, or a plurality of them may be combined and applied by AND and OR conditions in combination. The X, Y, and Z values are preset values according to the type of words stored in the word database 102 and the difficulty of the game, and can be appropriately selected according to the embodiment.

The reason for excluding candidate words whose average of document frequencies is a certain value or more is that words starting with the end syllables of the candidate words are frequently used words. In addition, the reason for excluding candidate words having a standard deviation of a predetermined value or more is that the document frequency values of some of the words starting with the end syllables of the candidate words appear very large. In the case of words having a maximum value equal to or greater than a certain value, a word that is used very frequently is mixed with a word that starts with the end syllable of the candidate word. That is, in the exemplary embodiment of the present invention, the difficulty of the game is increased by excluding a candidate word including a word frequently used even if some of the words are frequently used in view of the document frequency of words beginning with the end syllable of the candidate word.

In the above example, since there are only two candidate words included in the candidate word group, "student" and "school class", it is assumed that no words are excluded in this step.

Next, the sum of the document frequencies calculated for each candidate word is normalized to a value between 0 and 1 (212). The normalization may be performed using Equation 2 below.

Where S (i) is the sum of document frequencies of words starting with the end syllable of candidate word i, S _N (i) is the sum of normalized document frequencies, and max (S) starts with the end syllable of each candidate word. It is the maximum of the sum of the document frequencies of the words. The higher the frequency of literature, the lower the value, and the lower the frequency of literature, the higher the value.

In the above example, since the sum of the document frequencies calculated for each candidate word is 120 and 20, respectively, and the maximum value is 120, normalizing the sum of the document frequencies is as follows.

Sum of normalized document frequencies for each candidate word = [0, 0.833]

On the other hand, it is possible to determine the level of game desired by the user at the start of the game. The level of the game can be set to [top or bottom], for example, or a number from 1 to 10 can be used. At this time, the difficulty of the word can be adjusted according to the level of the game. The average difficulty, minimum difficulty, and highest difficulty of words beginning with the end of the candidate words can be used together to make the game high or low. For example, the average difficulty of the words may be determined according to the level of the game, the minimum difficulty may be above a certain value, and the maximum difficulty may be below a certain value, thereby excluding candidate words that deviate therefrom. In this case, the highest and lowest difficulty may be determined by applying a standard deviation from the mean. By setting the mean and standard deviation, the appropriate words are selected accordingly.

Next, for each candidate word, an average difficulty level of words having end syllables as starting syllables of each candidate word is obtained (214).

In the above example, the difficulty levels of words starting with the end syllable of "student" among the candidate words, that is, "life", "living water", and "life" are 0.2, 0.4, and 0.6, respectively, and their average difficulty is 0.4. In addition, since the difficulty of the words "beginning with the end syllable of the" school bell "among the candidate words," religion "and" end ", is 0.9 and 0.9, respectively, the average difficulty is 0.9.

Average Difficulty for Each Candidate Word = [0.4, 0.9]

From the average, standard deviation, and minimum value of the difficulty of each candidate word, if the mean is below a certain value (U), the standard deviation is above a certain value (V), or the minimum value is below a certain value (W), the corresponding candidate word is selected. It excludes from the candidate word group. At this time, each of these may be applied alone, or a plurality of them may be combined and applied by AND and OR conditions in combination. In addition, the U, V, and W values are preset values according to the type of words stored in the word database 102 and the difficulty of the game, and can be appropriately selected according to embodiments.

Next, the goodness of fit of each candidate word is calculated using the sum of the normalized document frequencies and the average difficulty (216). The goodness of fit may be calculated by Equation 3 below.

Where i is the candidate word, R (i) is the goodness of fit of candidate word i, S _N (i) is the sum of normalized document frequencies of words starting with the end syllable of candidate word i, and D (i) is candidate word i the average degree of difficulty of the words that start with the end of a syllable, w ₁ and w ₂ is w ₁ + w ₂ = ₁ as a weight (adjustment coefficient) of each reference frequency and degree of difficulty. The adjustment coefficient can be appropriately determined according to specific embodiments, and it can be seen that the higher the w ₁ , the higher the specific gravity (weighting) of the document frequency, and the higher the w ₂ , the higher the specific gravity is for the difficulty.

Finally, the candidate word having the highest calculated goodness of fit is selected as the end of the inputted present word (218). When there are a plurality of words having the highest suitability, they may be arbitrarily selected, or may be determined according to the ranking of some of the various conditions.

In the above example, if w ₁ = w ₂ = 0.5, the fitness of the "student" is 0.2 and the fitness of the "school class" is 0.867. This means that the word beginning with the end of the "school bell" is less frequent and more difficult than the word beginning with the end of the "student." Therefore, the word output unit 108 selects "school type".

3 is a diagram illustrating a word game device 100 according to another embodiment of the present invention.

As shown, the word game apparatus 300 according to another embodiment of the present invention, the word database 302, the start frequency database 304, the user input unit 306, the word selector 308 and the word output unit 310 is configured to include.

The word database 302 is a database in which a plurality of words, a document frequency of each word, and difficulty information of each word are stored. The word database 302 stores a plurality of words and difficulty information of each word. As a database, the word database 102 shown in FIG. 1 has a configuration in which the document frequency field is excluded. According to this embodiment, since the document frequency does not need to be determined separately, it is easy to apply. The word database 302 may be configured, for example, as shown in Table 2 below.

word difficulty bag 0.1 Go 0.1 Vacation 0.2 life 0.2 bottled water 0.4 life 0.6 religion 0.9 Termination 0.9 student 0.1 School bell 0.2

The starting frequency database 304 stores the first syllable of every word stored in the word database 302 and the frequency in the word database of words starting with the first syllable. The starting frequency database 304 may be configured, for example, as shown in Table 3 below.

First syllable Starting frequency end 2 room One student 3 Bell 2 crane 2

In the items of Table 3, "first syllable" indicates the first syllable of words stored in the word database 302, and "start frequency" indicates the frequency of the word database 302 of words starting with each first syllable. For example, in Table 3, the starting frequency of "live" is "3", indicating that there are a total of three words starting "live" in the word database 302.

The user input unit 306 receives a suggestion from a user. Since the configuration of the user input unit 306 in this embodiment is substantially the same as that of the user input unit 104 described with reference to FIG. 1, the detailed description thereof is omitted here.

The word selector 308 selects one of the words in the word database 302 starting with the end syllable of the word (suggested word) input from the user input unit 306. In detail, the word selector 308 extracts words beginning with the end syllable of the inputted present word from the word database 302 to generate a candidate word group and for each candidate word included in the candidate word group. The number of words having the first syllable as the first syllable is extracted from the start frequency database 304, and the number of start frequencies extracted from the start frequency database 304 among the candidate words included in the candidate word group and the word database. Choose a word considering the difficulty of A detailed word selection process in the word selector 308 will be described in detail with reference to FIG. 4.

The word output unit 310 displays the word selected by the word selector 308 to the user.

4 is a flowchart illustrating a word selecting method 400 of the word game apparatus 300 according to another exemplary embodiment.

First, when the user input unit 306 receives a suggestion from the user (402), the word selector 308 extracts words starting with the end syllable of the inputted present word from the word database to generate a candidate word group (404). ).

For example, when the presentation received from the user input unit 306 is "vacation", the end syllable is "hak". In the word database 306 illustrated in Table 1, the words "study" as the first syllable are "student" and "school class", so the two words are candidate word groups that can be presented as the end of the present word.

Next, a frequency (starting frequency) in the word database 302 of a word having the first syllable as the first syllable for each candidate word included in the candidate word group is extracted from the starting frequency database 304. (406).

In the above example, the starting frequency of "live" which is the last syllable of "student" is 3, and the starting frequency of "species" which is the last syllable of "school species" is 2.

In this case, when a starting frequency for each candidate word is equal to or greater than a predetermined value T, the candidate word may be excluded from the candidate word group. If the start frequency is large, it means that the number of words that start at the end of the candidate word is large. The T value is a value which is set in advance according to the type of words stored in the word database 302 and the difficulty of the game, and can be appropriately selected according to the embodiment.

Next, each start frequency extracted in step 406 is normalized to have a value between 0 and 1 (408). The normalization may be performed using Equation 4 below.

Where i is a candidate word, B (i) is the start frequency of words having the first syllable as the first syllable, max (B) is the maximum start frequency, and B _N (i) is the normalized start frequency to be. As can be seen from the above equation, the smaller the starting frequency, the larger the value of B _N (i), and the larger the starting frequency, the smaller the B _N (i).

In the above example, the normalized starting frequency of words beginning with the first syllable of the end syllables of the candidate words ("student" and "school class") is as follows.

Normalized starting frequency for each candidate word = [0, 0.333]

In this case, from the average, standard deviation, and minimum value of the difficulty of each candidate word, if the average is less than a certain value (U), the standard deviation is more than a certain value (V), or the minimum value is less than or equal to a certain value (W) The words may be excluded from the candidate word group. In this case, each of them may be applied alone, or a plurality of words may be combined and applied by the AND and OR conditions. In addition, the U, V, and W values are preset values according to the type of words stored in the word database 102 and the difficulty of the game, and can be appropriately selected according to embodiments.

Next, the average difficulty of words beginning with the first syllable and ending syllable of each candidate word is calculated using a word database (410).

 In the above example, the average difficulty of words beginning with the first syllable of the end syllables of candidate words ("student" and "school bell") is as follows. First, among the candidate words, words starting with the end syllable of "student", that is, "life", "living water", and "life" have difficulty levels of 0.2, 0.4, and 0.6, respectively, and their average difficulty is 0.4. In addition, since the difficulty of the words "beginning with the end syllable of the" school bell "among the candidate words," religion "and" end ", is 0.9 and 0.9, respectively, the average difficulty is 0.9.

Average difficulty for each candidate word = [0.4, 0.9]

Next, a goodness of fit of each candidate word is calculated (412), and the candidate word having the highest calculated goodness of fit is selected as the end of the inputted suggestion (414).

The goodness of fit may be calculated by the following Equation 5.

Where i is the candidate word, G (i) is the goodness of fit of candidate word i, B _N (i) is the normalized starting frequency of words starting with the end syllable of candidate word i, and A (i) is the end of candidate word i The average difficulty of words beginning with syllables, w ₃ and w _4, are w ₃ + w ₄ = 1 as the weights (adjustment coefficients) of the starting frequency and difficulty, respectively. The adjustment coefficient can be appropriately determined according to the specific embodiment, and it can be seen that the higher the w ₁ , the higher the specific gravity (weighting value) of the starting frequency, and the higher the w ₂ , the higher the specific gravity is for the difficulty.

In the above example, if w ₃ = w ₄ = 0.5, the fitness of the "student" is 0.2 and the fitness of the "school class" is 0.617. Therefore, the word output unit 310 selects the "school type" as the end. If there is a tie in the goodness of fit, it can be chosen arbitrarily or by adjusting the weight of the starting frequency and difficulty.

On the other hand, even in this embodiment, it is possible to determine the level of the game desired by the user at the start of the game. The level of the game may be, for example, one of the top or bottom, or a number from 1 to 10. At this time, the difficulty of the word can be adjusted according to the level of the game. The average difficulty, minimum difficulty, highest difficulty, and standard deviation of the words starting with the end of the candidate words can be used to make the game higher or lower. For example, the average difficulty of the words may be determined according to the level of the game, the minimum difficulty may be above a certain value, and the maximum difficulty may be below a certain value, thereby excluding candidate words that deviate therefrom. In this case, the highest and lowest difficulty may be determined by applying a standard deviation from the mean. By setting the mean and standard deviation, the appropriate words are selected accordingly.

On the other hand, as another embodiment of the present invention, by changing the above equation may be applied to the document frequency, starting frequency and difficulty. In this case, the word database consists of (word, document frequency, difficulty) fields, and the start frequency database consists of (first syllable, starting frequency) fields. The goodness of fit may use Equation 6 as follows.

Where i is the candidate word, E (i) is the goodness of fit of candidate word i, F (i) is the sum of normalized document frequencies of words starting with the end syllable of candidate word i, and D (i) is The average difficulty of words beginning with the end syllable, N (i) is the normalized starting frequency of the words beginning with the end syllable of candidate word i, w _{5 ,} w _{6 ,} w ₇ are the weights of the document frequency and the starting frequency and difficulty, respectively As an adjustment factor, w ₅ + w ₆ + w ₇ = 1. The said adjustment coefficient can be suitably determined according to specific embodiment.

Before applying the equation, if the criteria, difficulty, and starting frequency of each candidate word do not satisfy a predetermined criterion in the mean, standard deviation, and minimum value (or maximum value), the candidate word is excluded from the candidate word group. can do. At this time, each of these may be applied alone, or a plurality of them may be combined and applied by AND and OR conditions in combination.

Meanwhile, an embodiment of the present invention may include a computer readable recording medium including a program for performing the methods described herein on a computer. The computer-readable recording medium may include program instructions, local data files, local data structures, etc. alone or in combination. The media may be those specially designed and constructed for the purposes of the present invention, or they may be of the kind well-known and available to those having skill in the computer software arts. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tape, optical recording media such as CD-ROMs, DVDs, magnetic-optical media such as floppy disks, and ROM, RAM, flash memory, and the like. Included are hardware devices specifically configured to store and execute program instructions. Examples of program instructions may include high-level language code that can be executed by a computer using an interpreter as well as machine code such as produced by a compiler.

Although the present invention has been described in detail with reference to exemplary embodiments above, those skilled in the art to which the present invention pertains can make various modifications to the above-described embodiments without departing from the scope of the present invention. Will understand.

Therefore, the scope of the present invention should not be limited to the described embodiments, but should be defined by the claims below and equivalents thereof.

1 is a diagram showing a word game device 100 according to an embodiment of the present invention.

2 is a flowchart illustrating a word selecting method 200 of the word game apparatus 100 according to an exemplary embodiment.

3 is a diagram illustrating a word game device 100 according to another embodiment of the present invention.

4 is a flowchart illustrating a word selecting method 400 of the word game apparatus 300 according to another exemplary embodiment.

Claims (30)

A word database storing a plurality of words, a document frequency of each word, and difficulty information of each word; A user input unit configured to receive a suggestion from a user; Words starting from the input syllables of the input word are extracted from the word database to generate candidate word groups, and for each of the candidate words included in the candidate word groups, the end syllables of each candidate word as starting syllables. A word selector which extracts document frequency and difficulty information of the word from the word database, and selects one word among the candidate words by comparing the document frequency and difficulty information of the extracted words; And A word output unit which displays the word selected by the word selector to the user; Word game device that includes. The method of claim 1, The difficulty level of each word stored in the word database is proportional to the number of letters of each word. The method of claim 1, The difficulty level of each word stored in the word database is proportional to the level of each word in an ontology composed of words stored in the word database. The method of claim 1, Difficulty of each word stored in the word database is the following equation,

Wherein A is a word, D _i is the difficulty of the document in which the word A appears, and F _i is the frequency of the word A in the document D _i . The method of claim 1, The word selection unit, For each of the retrieved candidate words, the following equation

Where i is the candidate word, R (i) is the goodness of fit of candidate word i, S _N (i) is the sum of normalized document frequencies of words starting with the end syllable of candidate word i, and D (i) is the candidate word The average difficulty of words starting with the ending syllable of i, w ₁ and w ₂ are the weights (coordination coefficients) of document frequency and difficulty, respectively, w ₁ + w ₂ = 1) Calculating a goodness of fit of each of the retrieved candidate words, and selecting the candidate word having the highest calculated goodness of fit. The method of claim 5, S _N (i) is represented by the following equation

Where S (i) is the sum of the document frequencies of words starting with the end syllable of candidate word i and max (S) is the maximum of the sum of document frequencies of the words beginning with the end syllable of each candidate word. Calculated by the word game device. The method of claim 5, The word selection unit, Words included in the candidate word group Calculate the average, standard deviation, and maximum of the document frequency of the words among the candidate words whose end syllables are the first syllables, and the average is equal to or greater than a preset value. And if the standard deviation is greater than or equal to a preset value, or if the maximum value is greater than or equal to a predetermined value, the candidate word is excluded from the candidate word group. A word database storing a plurality of words and difficulty information of each word; A start frequency database in which the frequency of the first syllable of all words stored in the word database and the word database of words starting with the first syllable is stored; A user input unit configured to receive a suggestion from a user; Words starting from the input syllables of the input word are extracted from the word database to generate a candidate word group, and a word having the first syllable as the first syllable for each candidate word included in the candidate word group. Extracts the number of times from the start frequency database, extracts a difficulty level of the word having the first syllable as the first syllable from the word database, compares the extracted start frequency and the difficulty information, and then selects one of the candidate words. A word selector for selecting a word of the word; And A word output unit which displays the word selected by the word selector to the user; Word game device that includes. The method of claim 8, And the word selecting unit excludes the candidate word from the candidate word group when the starting frequency extracted from the starting frequency database among the candidate words is equal to or greater than a predetermined value. The method of claim 8, The word selection unit, For each of the retrieved candidate words, the following equation

Where i is the candidate word, G (i) is the goodness of fit of candidate word i, B _N (i) is the normalized starting frequency of words starting with the end syllable of candidate word i, and A (i) is The average difficulty of words beginning with the end syllable, w ₃ and w ₄ are the weights (adjustment coefficients) of the starting frequency and difficulty, respectively, as w ₃ + w ₄ = 1) Calculating a goodness of fit of each of the retrieved candidate words, and selecting the candidate word having the highest calculated goodness of fit. The method of claim 10, The B _N (i) is the following equation,

(Where i is the candidate word, B (i) is the starting frequency of words having the first syllable as the first syllable, and max (B) is the maximum value of the starting frequency) Calculated by the word game device. A word database storing a plurality of words, a document frequency of each word, and difficulty information of each word; A start frequency database in which the frequency of the first syllable of all words stored in the word database and the word database of words starting with the first syllable is stored; A user input unit configured to receive a suggestion from a user; Words starting from the input syllables of the input word are extracted from the word database to generate candidate word groups, and for each of the candidate words included in the candidate word groups, the end syllables of each candidate word as starting syllables. Extracts document frequency and difficulty information from the word database, extracts the number of words having the first syllable as the first syllable of each candidate word from each of the candidate words included in the candidate word group, from the starting frequency database, A word selector which selects one word among the candidate words by comparing document frequency, difficulty information, and start frequency information of the extracted words; And A word output unit which displays the word selected by the word selector to the user; Word game device that includes. The method of claim 12, The word selection unit, For each of the retrieved candidate words, the following equation

Where i is the candidate word, E (i) is the goodness of fit of candidate word i, F (i) is the sum of normalized document frequencies of words starting with the end syllable of candidate word i, and D (i) is candidate word i The average difficulty of words starting with the end syllable of N, i (i) is the normalized starting frequency of words starting with the ending syllable of candidate word i, w _{5 ,} w _{6 , and} w ₇ , respectively. As weight (adjustment factor) w ₅ + w ₆ + w ₇ = 1) Calculating a goodness of fit of each of the retrieved candidate words, and selecting the candidate word having the highest calculated goodness of fit. The method of claim 13, S _N (i) is represented by the following equation

Where S (i) is the sum of the document frequencies of words starting with the end syllable of candidate word i and max (S) is the maximum of the sum of document frequencies of the words beginning with the end syllable of each candidate word. Calculated by the word game device. The method of claim 13, The B _N (i) is the following equation,

(Where i is the candidate word, B (i) is the starting frequency of words having the first syllable as the first syllable, and max (B) is the maximum value of the starting frequency) Calculated by the word game device. As a word game method in a word game device, At the word game device, receiving a suggestion from a user; Generating, at the word game apparatus, candidate word groups by extracting words starting with the end syllables of the inputted present word from the word database; Extracting, from the word database, document frequency and difficulty information of a word having an end syllable as a starting syllable for each candidate word included in the candidate word group in the word game device; In the word game device, selecting one word of the candidate words by comparing the extracted document frequency and difficulty information; And Outputting the selected word in the word game device; Word game method that includes. The method of claim 16, The word selection step, Calculating a sum, mean, standard deviation, and maximum value of document frequencies of words having end syllables as starting syllables for each candidate word; The candidate word corresponding to the average is more than a certain value, the standard deviation is more than a certain value, or the maximum value is more than a certain value by using the sum, mean, standard deviation, and maximum value of the document frequencies calculated for each candidate word. Excluding from the candidate word group; Normalizing the sum of the document frequencies calculated for each candidate word; Calculating an average difficulty of words having end syllables as starting syllables for each candidate word for each candidate word; Calculating a goodness of fit of each candidate word using the sum of the normalized document frequencies and the average difficulty; And Selecting the candidate word having the largest calculated goodness of fit as the end of the presenting word. The method of claim 17, The sum of the normalized document frequencies is represented by the following equation

Where S _N (i) is the sum of normalized document frequencies, S (i) is the sum of document frequencies of words starting with the end syllable of candidate word i, and max (S) is the end syllable of each candidate word. The maximum of the sum of the document frequencies of the starting words) Calculated by, the word game method. The method of claim 17, The goodness of fit is the following equation

Where i is the candidate word, R (i) is the goodness of fit of candidate word i, S _N (i) is the sum of normalized document frequencies of words starting with the end syllable of candidate word i, and D (i) is the candidate word The average difficulty of words starting with the ending syllable of i, w ₁ and w ₂ are the weights (coordination coefficients) of document frequency and difficulty, respectively, w ₁ + w ₂ = 1) Calculated by, the word game method. As a word game method in a word game device, At the word game device, receiving a suggestion from a user; Generating, at the word game apparatus, candidate word groups by extracting words beginning with an end syllable of the inputted present word from the word database; Extracting, in the word game apparatus, a frequency (starting frequency) from the word database of a word having the first syllable as the first syllable of each candidate word for each of the candidate words included in the candidate word group; Extracting, from the word database, a difficulty level of a word having the first syllable as the first syllable in the word game device; In the word game device, selecting one word of the candidate words by comparing the starting frequency and difficulty information; And Outputting the selected word in the word game device; Word game method that includes. 21. The method of claim 20, The word selection step, Normalizing the starting frequency extracted in the frequency extraction step; Calculating an average difficulty of words having end syllables as starting syllables for each candidate word for each candidate word; Calculating a goodness of fit of each candidate word using the normalized starting frequency and the average difficulty; And Selecting a candidate word having the largest calculated goodness of fit as the end of the predicate; Word game method that includes more. The method of claim 21, The normalized starting frequency is the following equation

Where i is the candidate word, B (i) is the starting frequency of words that have the first syllable as the first syllable, max (B) is the maximum value of the starting frequency, and B _N (i) is the normalized starting frequency ) Calculated by, the word game method. The method of claim 21, The said goodness of fit is the following formula

Where i is the candidate word, G (i) is the goodness of fit of candidate word i, B _N (i) is the normalized starting frequency of words starting with the end syllable of candidate word i, and A (i) is The average difficulty of words beginning with the end syllable, w ₃ and w ₄ are the weights (adjustment coefficients) of the starting frequency and difficulty, respectively, as w ₃ + w ₄ = 1) Calculated using the word game method. As a word game method in a word game device, At the word game device, receiving a suggestion from a user; Generating, at the word game apparatus, candidate word groups by extracting words beginning with an end syllable of the inputted present word from the word database; Extracting, from the word database, document frequency and difficulty information of a word having an end syllable as a starting syllable for each candidate word included in the candidate word group in the word game device; Extracting, in the word game apparatus, a frequency (starting frequency) from the word database of a word having the first syllable as the first syllable of each candidate word for each of the candidate words included in the candidate word group; In the word game device, selecting one word among the candidate words by comparing the extracted document frequency, difficulty information, and starting frequency; And Outputting the selected word in the word game device; Word game method that includes. The method of claim 24, The starting frequency extraction step, And removing the candidate word from the candidate word group when the starting frequency extracted from the starting frequency database among the candidate words is greater than or equal to a predetermined value. The method of claim 25, The word selection step, Calculating a sum of document frequencies of words having starting syllables as end syllables of each candidate word for each candidate word; Normalizing the sum of the document frequencies calculated for each candidate word; Calculating an average difficulty of words having end syllables as starting syllables for each candidate word for each candidate word; Normalizing the starting frequency extracted in the frequency extraction step; Calculating a goodness of fit of each candidate word using the sum of the normalized document frequencies, the average difficulty, and the normalized starting frequency; And Selecting the candidate word having the largest calculated goodness of fit as the end of the presenting word. The method of claim 26, The sum of the normalized document frequencies is represented by the following equation

Where S _N (i) is the sum of normalized document frequencies, S (i) is the sum of document frequencies of words starting with the end syllable of candidate word i, and max (S) is the end syllable of each candidate word. The maximum of the sum of the document frequencies of the starting words) Calculated by, the word game method. The method of claim 26, The normalized starting frequency is the following equation

Where i is the candidate word, B (i) is the starting frequency of words that have the first syllable as the first syllable, max (B) is the maximum value of the starting frequency, and B _N (i) is the normalized starting frequency ) Calculated by, the word game method. The method of claim 26, The said goodness of fit is the following formula

Where i is the candidate word, E (i) is the goodness of fit of candidate word i, F (i) is the sum of normalized document frequencies of words starting with the end syllable of candidate word i, and D (i) is candidate word i The average difficulty of words starting with the end syllable of N, i (i) is the normalized starting frequency of words starting with the ending syllable of candidate word i, w _{5 ,} w _{6 , and} w ₇ , respectively. As weight (adjustment factor) w ₅ + w _{6 +} w ₇ = 1) Calculated by, the word game method. A computer-readable recording medium having recorded thereon a program for performing the method according to any one of claims 16 to 29 on a computer.

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