CN104536588A - Keyboard associating method for navigation equipment using map data - Google Patents
Keyboard associating method for navigation equipment using map data Download PDFInfo
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- CN104536588A CN104536588A CN201410777986.3A CN201410777986A CN104536588A CN 104536588 A CN104536588 A CN 104536588A CN 201410777986 A CN201410777986 A CN 201410777986A CN 104536588 A CN104536588 A CN 104536588A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
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Abstract
A keyboard associating method for navigation equipment using map data comprises a character and word dividing method which comprises firstly defining priority levels which can be given to characters or words and accordingly conveniently performing statistics on results of the priority levels, wherein the importance degrees of map elements in retrieval are mainly considered through the defined priority levels. The keyboard associating method for the navigation equipment using the map data also comprises a keyboard associating function achievement method which comprises judging every time when a character phonetic alphabet is input to the keyboard, firstly judging whether all input alphabets can form into a word and finding all words according to single character if not. The keyboard associating method for the navigation equipment using the map data has the advantages that the navigation map data can be divided into meaningful characters and words, reasonable popular degrees are provided for the dividing results according to the importance degrees of contents inside the map data; the hit rate is greatly improved and the using experience of a user is increased due to the fact that the pinyin input method which is used in combination with specific scenes is guided to input characteristics and the words in a navigation input method.
Description
Technical field
The present invention relates to vehicle mounted guidance field, particularly a kind of navigator uses the keyboard association method of map datum.
Background technology
Input through keyboard is all functional realiey needing must to be comprised by the function of key search.The rationality of keyboard layout and whether provide association function, be two key characters that design keyboard needs to consider, wherein, the association function of keyboard is the emphasis of keyboard Designing.Contrary, the importance of this part is but easily out in the cold.
The association function of keyboard can assist us to input, and reduces input operation.And the candidate word that the prerequisite reducing operation is to provide is effective to user.If be not that user wants at the character/word being supplied to user, even user wants the word of selection in most cases later, and this will cause negative effect, causes user and more operates.
Therefore, above these can be summarized as: for definition and the division of keyboard candidate word, and which incites somebody to action alternatively word, and be supplied to user, which but can not.How reasonably to mark the temperature of word and the word occurred in keyboard association.The word high to temperature is preferentially supplied to user.
Summary of the invention
The object of the invention is to utilize map datum as main word library, and extract from key element different according to different candidate word, the temperature of definition initial word, spy provides the keyboard association method that a kind of navigator uses map datum.
The invention provides the keyboard association method that a kind of navigator uses map datum, it is characterized in that: described navigator uses the keyboard association method of map datum to comprise:
Divide the method for word and word:
First the priority level needing defined word or word to give, then facilitates next step to these priority, carries out statistics respectively.
Table 1. priority list
Priority emphasis defined above considers the significance level of map elements in retrieval.The key element higher to significance level or attribute are assigned to higher priority.
When definition priority, the present invention emphasizes the importance of user data in these data, is assigned to a very high priority to the content that user produces.User data is suggested in the present invention, is both different from map datum, and diagram data is used and processes in combination again.
The priority of all data sources, once determine, just can start second step.To the word in different pieces of information source, according to the entirety statistics frequency of occurrences.For the word segmented in different pieces of information source, according to the different pieces of information source statistics frequency of occurrences.Should be noted that: in word segmentation, need to control the length of word, it is generally acknowledged that the length of word is reasonable at 2 to 5 charactor comparisons, if exceed this length, just need artificial nucleus to consult the word of whether cutting not too reasonable.
After processing above, each word and word provide the attribute sorted during candidate just clear, respectively: priority, word length and frequency.Sequence will according to following rule:
When priority is different, the sequence that priority is high is forward.
When priority is identical, the short sequence of word length is forward.
When priority is identical with word length, the sequence that frequency is high is forward.
The temperature of word is described and will use this three indexs: priority, word length and frequency.
Described keyboard association function implementation method:
When keyboard inputs character phonetic alphabet at every turn, start to judge.First judge whether that inputting all letters can form word.If can not form word, all words will be searched according to individual character.
If searched according to individual character, needing to judge whether is the part of effective phonetic, and if find in individual character index, take out the temperature of the corresponding individual character of phonetic, according to the sequence of individual character temperature, provide candidate result; Otherwise, directly will provide candidate result according to input as English alphabet sequence.
If input all letters can form word, at least comprising a complete pinyin combinations and other letters, or two initial consonants and more than, below will search according to word, and if corresponding word can be found, the temperature sequence of word will be taken out, candidate result is provided.If do not found, also candidate result will be provided as English alphabet sequence.
This above process, can trigger because user constantly keys in new character and delete character.
Advantage of the present invention:
Navigator of the present invention uses the keyboard association method of map datum, according to navigation map data, can be divided into significant word and word, and utilize the significance level of content in map datum, provide rational temperature to these division results.Spelling input method input word and word is introduced in navigation input method, and unlike being only limitted to the input of individual character in the past, then coordinating candidate word and the word of map data creating, this special scenes of navigation uses, hit rate can be improved greatly, strengthen the experience of user.
Accompanying drawing explanation
Below in conjunction with drawings and the embodiments, the present invention is further detailed explanation:
Fig. 1 is the keyboard association method process flow diagram that navigator uses map datum.
Embodiment
Embodiment 1
The invention provides the keyboard association method that a kind of navigator uses map datum, it is characterized in that: described navigator uses the keyboard association method of map datum to comprise:
Divide the method for word and word:
First the priority level needing defined word or word to give, then facilitates next step to these priority, carries out statistics respectively.
Table 1. priority list
Priority emphasis defined above considers the significance level of map elements in retrieval.The key element higher to significance level or attribute are assigned to higher priority.
When definition priority, the present invention emphasizes the importance of user data in these data, is assigned to a very high priority to the content that user produces.User data is suggested in the present invention, is both different from map datum, and diagram data is used and processes in combination again.
The priority of all data sources, once determine, just can start second step.To the word in different pieces of information source, according to the entirety statistics frequency of occurrences.For the word segmented in different pieces of information source, according to the different pieces of information source statistics frequency of occurrences.Should be noted that: in word segmentation, need to control the length of word, it is generally acknowledged that the length of word is reasonable at 2 to 5 charactor comparisons, if exceed this length, just need artificial nucleus to consult the word of whether cutting not too reasonable.
After processing above, each word and word provide the attribute sorted during candidate just clear, respectively: priority, word length and frequency.Sequence will according to following rule:
When priority is different, the sequence that priority is high is forward.
When priority is identical, the short sequence of word length is forward.
When priority is identical with word length, the sequence that frequency is high is forward.
The temperature of word is described and will use this three indexs: priority, word length and frequency.
Described keyboard association function implementation method:
When keyboard inputs character phonetic alphabet at every turn, start to judge.First judge whether that inputting all letters can form word.If can not form word, all words will be searched according to individual character.
If searched according to individual character, needing to judge whether is the part of effective phonetic, and if find in individual character index, take out the temperature of the corresponding individual character of phonetic, according to the sequence of individual character temperature, provide candidate result; Otherwise, directly will provide candidate result according to input as English alphabet sequence.
If input all letters can form word, at least comprising a complete pinyin combinations and other letters, or two initial consonants and more than, below will search according to word, and if corresponding word can be found, the temperature sequence of word will be taken out, candidate result is provided.If do not found, also candidate result will be provided as English alphabet sequence.
This above process, can trigger because user constantly keys in new character and delete character.
Claims (2)
1. navigator uses a keyboard association method for map datum, it is characterized in that: described navigator uses the keyboard association method of map datum to comprise:
Divide the method for word and word:
First the priority level needing defined word or word to give, then facilitates next step to these priority, carries out statistics respectively; The priority emphasis of definition considers the significance level of map elements in retrieval; The key element higher to significance level or attribute are assigned to higher priority;
When definition priority, the present invention emphasizes the importance of user data in these data, is assigned to a very high priority to the content that user produces; User data is suggested in the present invention, is both different from map datum, and diagram data is used and processes in combination again;
The priority of all data sources, once determine, just can start second step; To the word in different pieces of information source, according to the entirety statistics frequency of occurrences; For the word segmented in different pieces of information source, according to the different pieces of information source statistics frequency of occurrences; Should be noted that: in word segmentation, need to control the length of word, it is generally acknowledged that the length of word is reasonable at 2 to 5 charactor comparisons, if exceed this length, just need artificial nucleus to consult the word of whether cutting not too reasonable;
After processing above, each word and word provide the attribute sorted during candidate just clear, respectively: priority, word length and frequency; Sequence will according to following rule:
When priority is different, the sequence that priority is high is forward;
When priority is identical, the short sequence of word length is forward;
When priority is identical with word length, the sequence that frequency is high is forward;
The temperature of word is described and will use this three indexs: priority, word length and frequency.
2. use the keyboard association method of map datum according to navigator according to claim 1, it is characterized in that: described navigator uses the keyboard association method of map datum, also comprises keyboard association function implementation method:
When keyboard inputs character phonetic alphabet at every turn, start to judge; First judge whether that inputting all letters can form word; If can not form word, all words will be searched according to individual character;
If searched according to individual character, needing to judge whether is the part of effective phonetic, and if find in individual character index, take out the temperature of the corresponding individual character of phonetic, according to the sequence of individual character temperature, provide candidate result; Otherwise, directly will provide candidate result according to input as English alphabet sequence;
If input all letters can form word, at least comprising a complete pinyin combinations and other letters, or two initial consonants and more than, below will search according to word, and if corresponding word can be found, the temperature sequence of word will be taken out, candidate result is provided; If do not found, also candidate result will be provided as English alphabet sequence; This process, can trigger because user constantly keys in new character and delete character.
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| CN201410777986.3A CN104536588B (en) | 2014-12-15 | 2014-12-15 | A kind of navigation equipment uses the keyboard association method of map datum |
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| CN201410777986.3A CN104536588B (en) | 2014-12-15 | 2014-12-15 | A kind of navigation equipment uses the keyboard association method of map datum |
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| CN104536588B CN104536588B (en) | 2017-05-31 |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111290677A (en) * | 2018-12-07 | 2020-06-16 | 中电长城(长沙)信息技术有限公司 | Self-service equipment navigation method and navigation system thereof |
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| CN101308030A (en) * | 2008-06-02 | 2008-11-19 | 凯立德欣技术（深圳）有限公司 | Chinese characters association method and Chinese characters association device using the method |
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| WO2010097144A1 (en) * | 2009-02-28 | 2010-09-02 | Bayerische Motoren Werke Aktiengesellschaft | Motor vehicle navigation system |
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| CN1783066A (en) * | 2004-11-29 | 2006-06-07 | 佛山市顺德区瑞图万方科技有限公司 | Method for establishing associated input system and correspondent associated input system and method |
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| WO2010097144A1 (en) * | 2009-02-28 | 2010-09-02 | Bayerische Motoren Werke Aktiengesellschaft | Motor vehicle navigation system |
| CN101794307A (en) * | 2010-03-02 | 2010-08-04 | 光庭导航数据（武汉）有限公司 | Vehicle navigation POI (Point of Interest) search engine based on internetwork word segmentation idea |
| CN102446195A (en) * | 2010-10-14 | 2012-05-09 | 环达电脑(上海)有限公司 | Method for displaying point of interest (PoI) search results |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111290677A (en) * | 2018-12-07 | 2020-06-16 | 中电长城(长沙)信息技术有限公司 | Self-service equipment navigation method and navigation system thereof |
| CN111290677B (en) * | 2018-12-07 | 2023-09-19 | 中电长城(长沙)信息技术有限公司 | Self-service equipment navigation method and navigation system thereof |
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| CN104536588B (en) | 2017-05-31 |
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Address after: 110000 No. 861-6, shangshengou village, Hunnan District, Shenyang City, Liaoning Province Patentee after: Shenyang Meihang Technology Co.,Ltd. Address before: 110004 Room 202, 1t international, No. 3, Yuanhang West Road, Hunnan New District, Shenyang, Liaoning Patentee before: SHENYANG MXNAVI Co.,Ltd. |