CROSS REFERENCE TO RELATED APPLICATIONS

This invention is related to commonly-assigned U.S. patent application Ser. No. 09/372,549 filed on the same day, of W. Chase for “System for Quantifying Intensity of Connotative Meaning;” commonly-assigned U.S. patent application Ser. No. 09/372,243 filed on the same day, of W. Chase for “Interactive Connotative Dictionary System;” commonly-assigned U.S. patent application Ser. No. 09/372,244 filed on the same day, of W. Chase for “Interactive Connotative Thesaurus System;” commonly-assigned U.S. patent application Ser. No. 09/372,737 filed on the same day, of W. Chase for “System for Connotative Analysis of Discourse.” The content of all such applications are incorporated herein by reference and made a part hereof.

BACKGROUND OF THE INVENTION

This invention relates to a system for identifying connotative meanings of words and phrases, and more particularly to a system for identifying emotional connotations associated with various words and phrases.

Symbolic representation is the use of ideas, images or other symbols to stand for objects or events. In the context of human language symbolic representation is achieved using words. The facility with symbolic representation to form languages distinguishes humankind from animals. Language is an abstract, rule-governed system of arbitrary symbols that can be combined in countless ways to communicate information. All languages include a system of phonology (i.e., set of sounds), semantics (i.e., word, phrase and sentence meanings), morphology (i.e., rules for combining smallest meaningful units to form or alter words), syntax (i.e., ways in which words are organized into phrases and sentences) and pragmatics (i.e., rules governing conversation and social use of language).

The use of language enables humankind to develop advanced cognitive abilities. Cognitive development relates to the changes in a person's memory, thinking, use of language and other mental skills as they develop from infants to adults. Humans develop a certain degree of cognitive competence. In addition to such cognitive competence, humans also display and experience feelings, emotions and moods. In particular, our emotional state or the emotional state we desire to elicit can influence our choice of words. Every human language enables people to communicate both intellectually and emotionally because words and phrases convey both cognitive and affective meaning. ‘Affective’ means to be influenced by or result from emotions.

Linguistics is the scientific study of language. Semantics is the branch of linguistics that deals with the study of the relationship between words or phrases and their meanings. Of particular significance here are the contrasting linguistic terms, denotation and connotation. ‘Denotation’ is a particular meaning of a symbol. ‘Connotation’ is an idea or meaning suggested by or associated with a word or phrase. Thus, ‘denote’ describes the relation between a word or phrase and the thing it conventionally names, whereas ‘connote’ describes the relation between the word or phrase and the images or associations it evokes. As used herein a denotation is an objective, cognitive meaning which refers to the direct relationship between a term and the object, idea or action it designates. As used herein, a connotation is a subjective, affective meaning which refers to the emotive and associative aspect of a term.

The denotative meanings of words have been systematically codified into definitions and collected together to form dictionaries, thesauruses and related denotative language references. However, the codification of connotative meanings has not been achieved. Consider, for example, a dictionary which provides the following denotative meaning for the word ‘pub’: “a building providing alcoholic drinks for consumption on the premises” (Oxford Dictionary). However, the word ‘pub’ simultaneously conveys a host of emotional connotations, such as merriment, pleasure, cheerfulness, perhaps some sadness, and so on. Similarly, words such as ‘summer’, ‘love’, and ‘melody’ have a variety of positive emotional connotative associations for most people, while words such as ‘cancer’, ‘rape’, and ‘homeless’ have negative emotional connotations for most people. In all cases, the associated connotations are not systematically accessible using any known language reference resource or tool.

The reason for the absence of codification of connotative meaning is that, while words readily evoke emotional connotations, the converse is not true: emotional connotations are not easily codified using words. Unlike denotative meaning, affective meaning does not naturally lend itself to systematic word-symbol description. Emotions are felt, not thought, so the relationship between a word and its associated connotative content, while real, is not codifiable using the relatively straightforward methods employed by lexicographers in fashioning denotative definitions.

Accordingly, there is a need of a system for codifying the connotative meanings of words and phrases. In particular there is a need for a ‘connotative meaning’ language reference tool.

SUMMARY OF THE INVENTION

According to the invention, a system for identifying connotative meaning of words or phrases is implemented. A given word or phrase has its connotative meaning determined for a given denotative context. A data base is formed having multiple records. Each record corresponds to a term (i.e., word or phrase) and its denotative context. Zero, one or more connotative associations are defined for each record.

According to another aspect of the invention, each record is evaluated by a plurality of connotative judges for a connotative association within a given emotional category. There are a predefined plurality of emotional categories established for evaluating connotative associations of terms. Within each emotional category there are a plurality of emotional descriptors.

According to one embodiment of the invention, there are eight emotional categories predefined for the English language: affection/friendliness, amusement/excitement, enjoyment/elation, contentment/gratitude, sadness/grief, anger/loathing, fear/uneasiness, and humiliation/shame. A plurality of descriptors are predefined for each emotional category.

According to another aspect of the invention, each connotative judge examines the denotative context of a given word or phrase and selects an emotional descriptor which the judge associates with such word or phrase in the given denotative context. The judge is given the emotional descriptors from a single category and selects the primary emotional descriptor, or both a primary and a secondary emotional descriptor which the judge associates with the word or phrase. Alternatively, the judge may indicate that none of the descriptors are associated with the word or phrase, or that the judge is unfamiliar with the word or phrase and its denotative context. In a separate analysis the judge is given the same or a different record. When the same record is presented, the judge is given a different set of emotional descriptors from a different emotional category. Again, the judge selects the primary emotional descriptor, or both a primary and a secondary emotional descriptor which the judge associates with the word or phrase. As with the prior record, the judge may indicate that none of the descriptors are associated with the word or phrase, or that the judge is unfamiliar with the word or phrase and its denotative context.

According to another aspect of the invention, each record is evaluated by a statistically significant number of judges for each one of the emotional categories. The results are processed to evaluate which emotional descriptors are most often associated with each given record. Anomalous results are purged (e.g., when the judge fills in responses at random rather than doing the mental work solicited; when the judge codes in many alternative responses such as ‘no connotative association’ or ‘unfamiliar with denotative context’). In a specific embodiment a statistical analysis is performed to assure that the selected emotional descriptors were not selected by chance. Where the emotional descriptor was selected enough times that the probability indicates it was not selected by chance, then the emotional descriptor is accepted as a connotative association for the word or phrase in the corresponding denotative context. Such association is retained in the database as part of the record for the word or phrase and its denotative meaning. Note that there may be 0, 1 or more connotative associations with any given record.

According to another aspect of the invention, the connotative associations are continuously updated, either at prescribed intervals or on an ongoing basis, such as through a World Wide Web site. In this way, connotative judges are able to supply data continuously, with turnover of connotative judges easily managed, and the database, particularly the connotative component, kept up to date with the changing times.

According to another aspect of the invention, a panel of judges is selected from a pool of judges to respond to a questionnaire. The questionnaire includes a plurality of records and allows selection of 0 or 1—or in some embodiments 2—emotional descriptors to be associated with any given record. The choices of emotional descriptors are limited to those in one emotional category. The same or a different panel of judges then evaluates the same plurality of records for a different emotional category. Eventually, each record is evaluated for each of the emotional categories by a desired number of connotative judges.

By practicing the above method and system of the present invention, a complete and accurate connotative language reference map and database is constructed in any language, which then can be used to construct connotative equivalents of denotative language reference resources, such as connotative dictionaries, connotative thesauruses, and connotative text analysis tools.

These and other aspects and advantages of the invention will be better understood by reference to the following detailed description taken in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1

is a block diagram of a host computer system;

FIG. 2

is a diagram of a connotative dictionary according to an embodiment of this invention;

FIG. 3

is a display sample of a user interface in ‘look up’ mode according to an embodiment of this invention;

FIG. 4

is another display sample of the user interface in ‘look up’ mode according to an embodiment of this invention;

FIG. 5

is a display sample of a user interface in ‘look for’ mode according to an embodiment of this invention;

FIG. 6

is another display sample of a user interface in ‘look for’ mode according to an embodiment of this invention;

FIG. 7

is yet another display sample of a user interface in ‘look for’ mode according to an embodiment of this invention; and

FIG. 8

is a diagram of a system for identifying connotative meanings according to an embodiment of this invention.

DESCRIPTION OF SPECIFIC EMBODIMENTS

A system and method are described for identifying, codifying, storing, and retrieving the connotative meaning inherent in the words and phrases of any language. Throughout this description, a preferred embodiment and examples given should be considered as exemplars rather than limitations on the method and system of the present invention.

Many of the functions of the present inventions preferably are performed by or with the assistance of a programmed digital computer of the type which is well known in the art, an example of which is shown in

FIG. 1. A

computer system

20

has a display

22

, a key entry device

24

, a pointing/clicking device

26

, a processor

28

, and random access memory (RAM)

30

. In addition there commonly is a communication or network interface

34

(e.g., modem; ethernet adapter), a non-volatile storage device such as a hard disk drive

32

and a transportable storage media drive

36

which reads transportable storage media

38

. Other miscellaneous storage devices

40

, such as a floppy disk drive, CD-ROM drive, zip drive, bernoulli drive or other magnetic, optical or other storage media, may be included. The various components interface and exchange data and commands through one or more busses

42

. The computer system

20

receives information by entry through the key entry device

24

, pointing/clicking device

26

, the network interface

34

or another input device or input port. The computer system

20

may be any of the types well known in the art, such as a mainframe computer, minicomputer, or microcomputer and may serve as a network server computer

12

, remote network

16

computer or a client computer

14

. The computer system

20

may even be configured as a workstation, personal computer, network server, or a reduced-feature network terminal device.

The connotative language reference serves as an interactive electronic connotative dictionary, thesaurus or other language reference. For a connotative dictionary embodiment; the connotative dictionary is distinct from a ‘classic’ dictionary in that it lists words with their connotative meanings. For a connotative thesaurus embodiment, the connotative thesaurus is distinct from a ‘classic’ thesaurus in that words are linked when they have the same or a similar emotional or related connotative meaning, but typically have a different denotative meaning. These linked words are referred to herein as “connonyms,” a coined word meaning connotative synonyms. The data bases forming a computer version of the connotative language references may be formed using custom-designed database software or database software commercially available from manufacturers such as Inprise, Oracle, Microsoft or another vendor of data base software services.

Following are sections which describe a preferred embodiment of a connotative language reference and a system for identifying connotative meanings.

Connotative Language Reference

Referring to

FIG. 2

, a connotative language reference system

10

is formed by a data base

12

, a user interface

14

and various filtering and retrieval processes

16

. Preferably such data base

12

, interface

14

and processes

16

are implemented in electronic format as one or more software programs executed on a host computer system or over a host computer network. For example, the reference system

10

may be stored on an optical disc (e.g., CD-ROM) or other storage media and installed onto a host computer system or network. Specifically, the data base

12

, user interface software

14

and filtering and retrieval processes

16

may be loaded and installed locally onto the host computer system or network. In some implementations the software embodying the user interface

14

and processes

16

are installed to be resident on the host computer system or network, while the data base

12

is stored and accessed from a removable storage media, such as an optical disk. In other embodiments the data base

12

is centrally located among one or more network server computers, while the user interface software

14

and processes

16

are stored and executed from either a local end user computer system or remotely at the server computer. The implementations may vary from local copies for a given end user's access to one or more copies stored on a private network or even a global computer network which users log into to access and use the dictionary.

Data Base

12

In a preferred embodiment of the data base

12

, the data base

12

includes a set of denotative fields

44

, a set of connotative fields

46

, and a set of human interest fields

48

. The denotative fields and human interest fields are not necessary, but provide additional resources for the user. In some embodiments the data base

12

includes only the set of connotative fields

46

.

The set of denotative fields

44

includes at least three fields. In one implementation the denotative data is obtained from one or more electronic or print-based dictionaries in any language. Database records are created for each word or phrase of the language, which may be the English language or any other language. In some embodiments the connotative language reference system

10

is specialized for a given subject (e.g., medical/health contexts; science). In other embodiments a general language reference is implemented for a given language. Table 1 below list three types of fields included among the denotative fields:

TABLE 1

Denotative Field Types

1.

Term (i.e., Word or phrase/idiom)

2.

Specific denotative context

3.

Part of speech

For each record in the data base

12

, one denotative field is assigned to a specific term, such as a word or phrase. A second denotative field is assigned to the denotative context (dictionary meaning) of the term. A third denotative field is assigned to the part of speech of the term of field

1

when used in the context of field

2

. Preferably, each context of each term is assigned a separate database record. Thus, if the dictionary definition of a single term has two meanings among a total of five contexts, then there are five records, one for each context. There may be multiple contexts for a given dictionary meaning when, for example, there are different parts of speech for the term.

Assigning an additional field to track the meanings that subsume the contexts is not necessary to practice the invention, but such a field may be assigned in an alternative embodiment. The total number of records included in the database

12

typically is equal to the sum of all of the denotative contexts of all of the terms obtained from the denotative data source or sources.

In a preferred embodiment the set of connotative fields

46

includes a block of one or more fields corresponding to each one of a plurality of emotional categories. In a best mode embodiment eight emotional categories have been identified, although the number of categories may vary to be more or less than eight. The number of fields comprising each block may vary. In one embodiment there is one field in each block that corresponds to a primary connotative emotional descriptor for the corresponding term. In some embodiments there is a field for storing a secondary connotative emotional descriptor for the corresponding term. Note that the primary and or secondary emotional descriptor can correspond to a designation of no connotative meaning stored in this emotional category for the given term.

In addition to the fields for the primary and optional secondary emotional descriptors, there also are fields associated with each block relating to the method for identifying connotative meaning. Although the method for defining connotative meaning may vary, in one embodiment the data is collected from multiple sources. In a given implementation the sources are judges or panels of judges. In some embodiments there is a field in each block for each judge's selection of the term's connotative meaning. In an example, where 24 connotative judges are used, each of the eight blocks of fields

46

includes 24 individual fields used in deriving the primary and/or secondary emotional descriptor for the term—a respective field to hold each judge's emotional descriptor data for each term in each context. Several additional fields are reserved to hold calculated data based on the connotative judges' emotional descriptor data. Fewer or more judges may be used, adjusting the number of fields within each block accordingly.

Table 2 lists eight emotional categories corresponding to the eight blocks of fields

46

for a best mode embodiment. In the exemplary embodiment the categories are classified into categories for positive emotions and categories for negative emotions. The general emotional classification “Positive Emotions” subsumes four emotional categories, and the general emotional classification “Negative Emotions” subsumes the other four emotional categories, as practiced in a preferred embodiment of the invention. Each emotional category subsumes a list of specific emotional descriptors (e.g., in this embodiment there are 12 to 37 emotional descriptors per category), each of which is associated with a two-digit identifying code number. The specific code number may vary. Further, the manner in identifying the distinct descriptors also may vary. The total number of emotional descriptors in this example is 164. In various embodiments one or more emotional descriptors may be removed from this list, entire emotional categories may be removed from the list, or one or more emotional categories and descriptors may be added to this list. In a preferred embodiment it is the code numbers which are stored in the records of the data base

12

. In other embodiments the entire emotional descriptor term may be stored individually for each connotative data field of a record.

The connotative emotional descriptors that appear in Table 2 are English language emotional descriptors for one embodiment of a general connotative dictionary. The specific words that make up the emotional connotative descriptors may vary. Of course such descriptors will vary from language to language.

TABLE 2

Connotative Database Fields

POSITIVE EMOTIONS:

Affection/Friendliness

01

Adoration

02

Affection

03

Amorousness

04

Devotion

05

Fondness

06

Friendliness

07

Infatuation

08

Kindliness

09

Liking

10

Love

11

Lust

12

Passion

13

Tenderness

14

Trust

15

Warmth

Amusement/Excitement

01

Amazement

02

Amusement

03

Astonishment

04

Eagerness

05

Enthusiasm

06

Excitement

07

Exhilaration

08

Exuberance

09

Fun

10

Glee

11

Hilarity

12

Merriment

13

Mirth

14

Surprise

15

Thrill

16

Wonder

Enjoyment/Elation

01

Admiration

02

Bliss

03

Cheer

04

Delight

05

Ecstasy

06

Elation

07

Enjoyment

08

Euphoria

09

Exultation

10

Happiness

11

Joy

12

Jubilation

13

Pleasure

14

Pride

15

Rapture

Contentment/Gratitude

01

Appreciation

02

Comfort

03

Contentment

04

Gladness

05

Gratitude

06

Hope

07

Peacefulness

08

Relief

09

Satisfaction

10

Serenity

11

Thankfulness

12

Well-being

NEGATIVE EMOTIONS

Sadness/Grief

01

Affliction

02

Agony

03

Anguish

04

Dejection

05

Demoralization

06

Depression

07

Desolation

08

Despair

09

Despondency

10

Disappointment

11

Discouragement

12

Disheartenment

13

Disillusionment

14

Dismay

15

Distress

16

Downheartedness

17

Forlornness

18

Gloom

19

Grief

20

Heartache

21

Heartbreak

22

Heartsickness

23

Hopelessness

24

Hurt

25

Longing

26

Melancholy

27

Misery

28

Pain

29

Pity

30

Sadness

31

Sorrow

32

Suffering

33

Torment

34

Unhappiness

35

Wretchedness

36

Yearning

Fear/Uneasiness

01

Alarm

02

Anxiety

03

Apprehension

04

Desperation

05

Distress

06

Dread

07

Fear

08

Horror

09

Nervousness

10

Panic

11

Paranoia

12

Stress

13

Tension

14

Terror

15

Uneasiness

16

Worry

Anger/Loathing

01

Abhorrence

02

Acrimony

03

Aggravation

04

Anger

05

Animosity

06

Annoyance

07

Antagonism

08

Antipathy

09

Aversion

10

Bitterness

11

Contempt

12

Creepiness

13

Detestation

14

Dissatisfaction

15

Disdain

16

Disgust

17

Dislike

18

Enmity

19

Envy

20

Exasperation

21

Frustration

22

Fury

23

Hatred

24

Hostility

25

Irritation

26

Indignation

27

Ire

28

Jealousy

29

Loathing

30

Offense

31

Outrage

32

Rage

33

Rancor

34

Resentment

35

Vexation

36

Virulence

37

Wrath

Humiliation/Shame

01

Chagrin

02

Contrition

03

Degradation

04

Discredit

05

Disgrace

06

Dishonor

07

Disrepute

08

Disrespect

09

Embarrassment

10

Guilt

11

Humiliation

12

Indignity

13

Mortification

14

Regret

15

Remorse

16

Shame

17

Stigma

In a preferred embodiment each record also includes a plurality of human interest fields

48

which each relate the corresponding term and its denotative context to a human interest category. The purpose of incorporating the human interest fields is to permit the end user to easily retrieve special connotative content from the database by first selecting one or more human interest filters before querying the database. The human interest fields

48

employed in an exemplary embodiment of the invention are listed in Table 3. There are nine groupings of the human interest categories in such embodiment. Each record includes a set of nine human interest fields—one field for each human interest category. Each field stores a human interest descriptor word. Of course, the field also may store a designation that there is no human interest context for the term as used in the associated denotative context of a given record. The human interest categories and descriptors may vary from embodiment to embodiment.

TABLE 3

SET 3: Human Interest Database Fields

Non-emotional Connotations

Power

Activity

Rhythm

Number of Syllables

Accented Syllable

Special Diction

Question-starting Words

Core Words Identified by S. I. Hayakawa

Personal Identity

Gender

First Names (Baby Names)

Notorious Or Celebrated People

Languages

National Identity

Organizations of Note

Home

Personal Relationships

Intimacy

Spiritual Identity

Biblical Diction

Christianity

Judaism

Islam

Hinduism

Buddhism

Other Religious

Myth and Legend

Paranormal

Physical Identity

Physical Appearance

Body

Health

Perception

Abstract/Concrete Continuum

Place, General

Place, Event

Place, Transportation

Place, Cosmos

Place, Noted

Color

Hearing

Touch

Taste

Smell

Time, General

Time, Historical

Time, Calendar

Non-medical Drug Use

Non-human Life

Animals

Plants

Micro Organisms

Argot/vernacular

Slang

Taboo

Offensive

Derogatory

Disgusting/Revolting

Euphemistic

Cliche

In a preferred embodiment of the invention, the assignment of the fields and records as described above effectively links each traditional dictionary definition of each term in each context with more than 200 connotative and human interest variables. Specifically, a given record identifies a denotative context and part of speech for a given word or phrase. Also associated with such record are one or more emotional descriptors from one or more emotional categories. Further, many records also may have one or more associated human interest descriptors.

In addition, there are additional miscellaneous fields defined in some embodiments. One such field is to store a rating for the degree of power which the term has in the associated denotative context. Another miscellaneous field is to store a rating of the degree of activity associated with the term in the corresponding denotative context. Yet another miscellaneous field is to store a rating along a scale spanning from concrete to abstract.

User Interface

14

In a preferred embodiment a graphical user interface is implemented, which provides an end user with the capability of retrieving data from the data base

12

. Although there are many ways in which a user interface may be implemented, in one embodiment a system with menus and windows is implemented.

Following is a description of a user interface for a connotative dictionary embodiment of the connotative language reference. Such user interface

14

is operated in either one of look-up mode or look-for mode. During ‘look-up’ mode a user enters a word or phrase and data is retrieved from the database

12

and displayed to the user. In ‘look for’ mode a user enters parameters into various filtering processes which are implemented to retrieve terms which correspond to criteria defined by the parameters.

FIG. 3

shows an embodiment of the graphical user interface

14

in ‘look up’ mode. The mode is indicated on a button

50

in the upper right corner of the interface window

52

. When in ‘look up’ mode, the user may type a word or phrase into a ‘look up’ box

54

in the upper left corner of the interface window

52

. The connotative dictionary responds to the user's typed input by retrieving denotative information from the database

12

relating to the word or phrase that has been typed into the ‘look up’ box

54

. This denotative information is displayed alphabetically in an area

55

(e.g., column) on the left-hand side of the user interface, and is formatted in much the same manner as the same denotative information is displayed and formatted in any conventional electronic dictionary.

Simultaneously, the dictionary

10

retrieves from the database

12

and displays on display

22

a range of connotative information relating to the same word or phrase that the user has typed in the ‘look up’ box

54

. This connotative information is displayed in an area

57

on the right-hand side of the user interface window

52

. Although specific formats and locations are being described the specific format and location of information within the window

52

may vary. In one embodiment the connotative information is displayed in a color-coded graphical format, including horizontal bars. Preferably, the relative lengths of the horizontal bars represent data corresponding to connotative intensity (strength or weakness). In one example, the colors designate the following:

Green (56)

Positive emotional connotations

Red (58)

Negative emotional connotations

Grey (60)

Connotations of power

Yellow (62)

Connotations of activity

Olive (64)

Connotations of abstractness or concreteness

A set of two tabs

61

,

63

, labeled “Level 1” and “Level 2,” indicate the level of emotional classification and categorization of the connotative data represented in the graphical display area

57

,

59

associated with the selected tab. In one embodiment these levels of classification and categorization are defined as follows:

Level 1: Four level 1 categories of “Positive Emotions” and four level 1 categories of “Negative Emotions” for the embodiment illustrated in FIG.

3

.

Level 2: Each level 1 emotional category subsumes a list of 12 to 37 specific emotional descriptors (e.g., level 2 information), as listed in Table 2. Only the level 2 emotional descriptors associated with the word displayed in the ‘Look up’ box are displayed.

FIG. 4

shows the user interface

14

in ‘look up’ mode with the level 2 data being displayed in window area

59

for a selected term highlighted in window area

55

. Such window area

59

overlays area

57

when tab

63

is selected.

FIGS. 5-7

show the user interface

14

in ‘look for’ mode. The user enters ‘look for’ mode by toggling the ‘Look up/Look for’ toggle button

50

. In a preferred embodiment of the invention, switching to ‘Look for’ mode changes the window

52

format to display a set of three tabs

66

,

68

,

70

with corresponding overlaying window areas

72

,

74

,

76

. These tabs and window areas replace the tabs

61

,

63

and window areas

57

,

59

of the ‘look up’ mode.

In ‘look for’ mode the user may retrieve connotative content from the database

12

. First, the user selects criteria from one or more human interest filters. Then the user initiates a search of the data base

12

for records matching the selected criteria. The human interest fields

48

employed in a preferred embodiment of the invention are listed in Table 3. These fields are displayed among the window areas

72

,

74

,

76

and are accessed by pressing on the corresponding tab

66

,

68

, or

70

. The number of tabs

66

,

68

,

70

and the allocation of human interest fields

48

to the window areas

72

,

74

,