Patent Publication Number: US-2016239561-A1

Title: System and method for obtaining information, and storage device

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
     This Non-provisional application claims priority under 35 U.S.C. §119(a) on Patent Application No(s). 104104845 filed in Taiwan, Republic of China on Feb. 12, 2015, the entire contents of which are hereby incorporated by reference. 
     BACKGROUND OF THE INVENTION 
     1. Field of Invention 
     The present invention relates to a system and method for obtaining information and, in particular, to a system and method for obtaining generalized term information, synonym information or homonym information. 
     2. Related Art 
     In most articles, especially in Chinese articles, the repeated terms are usually shown as abbreviations. For example, the term “ ” (Taiwan Railways Administration, pinyin: tai wan tie lu ju) has an abbreviation of “ ” (pinyin: tai tie ju). Moreover, the generic terms may increase and change with the history, culture and frequency. For instance, after the popularity of the famous “Facebook”, people in Taiwan will simply call it as “FB” or “  (pinyin: lian shu)”. The created synonyms and abbreviations can improve the communication efficiency and convenience, and further enrich the emotion expression. However, this is a difficult issue for the word/terminology process, which may fatally affect the searching results of all search engines. 
     For example, when a user wants to know about the term “ ” (army, pinyin: san jun) and googles it, the search results show a lot of information related to “ ” (Tri-service general hospital, pinyin: san jun zong yi yuan). Unfortunately, most of these results are not the desired answers for the user. Accordingly, the user may spend a lot of time to find out the desired information from the search results. This and similar problems exist in many situations. In brief, these generalized terms and abbreviations will decrease the searching efficiency of the search engine, thereby increasing the time spent of the user to discover the desired answers. 
     SUMMARY OF THE INVENTION 
     In view of the foregoing description, this invention is to provide a system, a method and an application for obtaining information that can improve the searching efficiency, thereby providing correct information with respect to the query term(s). 
     The present invention discloses a system for obtaining information, which includes a term creating unit, a term mapping unit, a database group and a user interface unit. The term creating unit links to a first server, which contains at least one first text file, and analyzes the first text file to generate at least one extracted term. The term mapping unit links to the term creating unit and a second server, which contains a plurality of second text files, and compares the extracted term with the second text files to determine to execute a generalized term extraction procedure, a synonym extraction procedure, or a homonym extraction procedure so as to correspondingly generate generalized term information, synonym information or homonym information. The database group links to the term creating unit and the term mapping unit, and stores the extracted term and the generated generalized term, synonym or homonym information. The user interface unit links to the database group ad receives a query term. When the query term matches the extracted term, the user interface unit provides the generalized term, synonym or homonym information. 
     In addition, this invention also discloses a method for obtaining information, which includes the following steps of: retrieving at least a first text file from a first server; analyzing the first text file to generate at least an extracted term; accessing a second server containing a plurality of second text files; comparing the extracted term with the second text files; and when at least one of the second text files contains the extracted term, executing a generalized term extraction procedure, a synonym extraction procedure, or a homonym extraction procedure so as to correspondingly generate generalized term information, synonym information or homonym information. 
     In one embodiment, the method for obtaining information further includes the steps of: when receiving a query term, comparing the query term to the extracted term to determine whether the query term matches the extracted term or not; and when the query term matches the extracted term, providing the generalized term, synonym or homonym information. 
     In one embodiment, the first server is a news server, and the first text file is a source code file of a news webpage. 
     In one embodiment, the step of generating the extracted term at least includes: retrieving a text content of the first text file; and executing a segmentation process with regard to the text content of the first text file so as to generate the extracted term. 
     In one embodiment, the segmentation process includes a lexicon segmentation method, a statistical segmentation method or a hybrid segmentation method. 
     In one embodiment, the second server is an open edit information server, and the second text file is an editable information webpage. 
     In one embodiment, the method for obtaining information further includes the steps of: determining whether the extracted term contains a number in a Chinese word; and if yes, executing the generalized term extraction procedure. 
     In one embodiment, when the text content of one of the second text files contains the extracted term, the generalized term extraction procedure includes: searching a location of the extracted term in the second text file; determining whether at least one specific character exists behind the extracted term in the second text file; if yes, determining whether the total number of the specific characters behind the extracted term matches the number in the Chinese word; and when the total number of the specific characters matches the number in the Chinese words, extracting terms in front of and behind the specific characters as the generalized term information. 
     In one embodiment, the specific character is a Chinese back sloping comma. In one embodiment, the step of determining whether the total number of the specific characters behind the extracted term matches the number in the Chinese word is to determine whether the total number of the terms in front of and behind the Chinese back sloping comma equals the number in the Chinese words minus one. 
     In one embodiment, when the text content of one of the second text files contains the extracted term, the synonym extraction procedure includes: searching a location of the extracted term in the second text file; and extracting the first term of the paragraph containing the extracted term as the synonym information. 
     In one embodiment, when the text content of one of the second text files contains the extracted term, the synonym extraction procedure includes: searching a location of the extracted term in the second text file; and extracting boldfaced words in the paragraph containing the extracted term as the synonym information. 
     In one embodiment, when the text content of one of the second text files contains the extracted term, the synonym extraction procedure includes: extracting a term located at a specific position in the second text file as the synonym information according to an editing rule of the second text file. 
     In one embodiment, when there are more than one of the second text files containing the extracted term, the homonym extraction procedure includes: processing the contents of the multiple second text files according to a term combination rule so as to generate the homonym information. 
     In one embodiment, the method for obtaining information further includes a step of: modifying the generalized term, synonym or homonym information according to an agree score; or modifying the generalized term, synonym or homonym information according to an input content. 
     In addition, the present invention further discloses a storage device storing an application, which is executed by a computer for performing the following steps of: retrieving at least a first text file from a first server; analyzing the first text file to generate at least an extracted term; accessing a second server containing a plurality of second text files; comparing the extracted term with the second text files; and when at least one of the second text files contains the extracted term, executing a generalized term extraction procedure, a synonym extraction procedure, or a homonym extraction procedure so as to correspondingly generate generalized term information, synonym information or homonym information. 
     Moreover, this invention also discloses a method for obtaining information, which includes the following steps of: receiving a query term; and when the query term contains a number in a Chinese word, providing generalized term information obtained according to a generalized term extraction procedure. 
     In one embodiment, the method for obtaining information further includes a step of: when the query term does not contain a number in a Chinese word, providing synonym information or homonym information obtained according to a synonym extraction procedure or a homonym extraction procedure. 
     As mentioned above, the method for obtaining information of this invention can retrieve at least one extracted term from the first text file of a first server, compare the extracted term with the second text files of a second server, and then execute a generalized term extraction procedure, a synonym extraction procedure, or a homonym extraction procedure according to the comparing result. As a result, this invention can improve the searching efficiency, thereby providing correct information with respect to the query term(s). 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The invention will become more fully understood from the detailed description and accompanying drawings, which are given for illustration only, and thus are not limited to the present invention, and wherein: 
         FIG. 1  is a block diagram showing a system for obtaining information according to a preferred embodiment of the invention; 
         FIG. 2  is a flow chart of a method for obtaining information according to a preferred embodiment of the invention; 
         FIG. 3  is a flow chart showing the details of a step S 24  of  FIG. 2 ; 
         FIG. 4  is a schematic diagram showing a table including extracted terms; 
         FIG. 5  is a flow chart showing the details of a step S 30  (a generalized term extraction procedure) of  FIG. 2 ; 
         FIG. 6A  is a schematic diagram showing the searching result according to a first embodiment of the invention; 
         FIG. 6B  is a schematic diagram showing the searching result according to a second embodiment of the invention; 
         FIG. 7  is a flow chart showing the steps of executing a synonym extraction procedure according to a first embodiment of the invention; 
         FIG. 8  is a flow chart showing the steps of executing a synonym extraction procedure according to a second embodiment of the invention; 
         FIG. 9  is a flow chart showing the steps of executing a synonym extraction procedure according to a third embodiment of the invention; 
         FIG. 10A  is a schematic diagram showing an information box; 
         FIG. 10B  is a flow chart showing the steps of executing a synonym extraction procedure according to a fourth embodiment of the invention; 
         FIG. 11  is a flow chart showing the steps of executing a homonym extraction procedure according to a preferred embodiment of the invention; 
         FIG. 12A  is a schematic diagram showing a displayed screen of the agree scores according to a preferred embodiment of the invention; 
         FIG. 12B  is a schematic diagram showing a displayed screen of adding terms according to a preferred embodiment of the invention; and 
         FIG. 12C  is a schematic diagram showing the generalized term information after adding the new terms according to a preferred embodiment of the invention. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     The present invention will be apparent from the following detailed description, which proceeds with reference to the accompanying drawings, wherein the same references relate to the same elements. 
       FIG. 1  is a block diagram showing a system  1  for obtaining information according to a preferred embodiment of the invention. Referring to  FIG. 1 , the system  1  includes a term creating unit  12 , a term mapping unit  14 , a database group  16 , and a user interface unit  18 . To be noted, the functional blocks of  FIG. 1  can be carried out by software, firmware and/or hardware (e.g. computers, chips, mobile devices, CPU, and the likes). 
     As shown in  FIG. 1 , the term creating unit  12  links to a first server  20 , which contains at least one first text file  202 . In this embodiment, the first server  20  is a news server, such as the server of Yahoo!News. Correspondingly, the first text file  202  is the source code file of a news webpage. 
     In addition, the term mapping unit  14  links to a second server  22 , which contains a plurality of second text files  222 . In some embodiments, the second server  22  is an open-edited information server, such as the Wikipedia server. Correspondingly, these second text files  222  can be multiple editable information webpages, such as the information webpages of the Wikipedia. Although the following embodiments are all based on Wikipedia, it should be known that the second server  22  can also be another kind of server, such as the Bidu server, Wikipedia Taiwan server, and the likes. 
       FIG. 2  is a flow chart of a method for obtaining information according to a preferred embodiment of the invention. With reference to  FIGS. 1 and 2 , the term creating unit  12  links to the first server  20  and then retrieves at least one first text file  202  (step S 22 ). Afterwards, the term creating unit  12  analyzes the first text file  202  to generate at least one extracted term  122  (step S 24 ). 
       FIG. 3  is a flow chart showing the details of the step S 24  of  FIG. 2 . With reference to  FIG. 3 , after retrieving the first text file  202 , the term creating unit  12  extracts the text content of the first text file  202  (step S 242 ). Then, the term creating unit  12  executes a segmentation process with regard to the text content of the first text file  202  so as to generate the extracted term (step S 244 ). 
     In  FIG. 3 , the step of executing a segmentation process (step S 244 ) can be carried out by a lexicon segmentation method, a statistical segmentation method or a hybrid segmentation method. In some embodiments, the step S 244  can be performed to execute a segmentation process with regard to the text content of the first text file  202  based on the CKIP segmentation system invented by Academia Sinica (Taiwan), thereby generating a plurality of extracted terms  122 .  FIG. 4  is a schematic diagram showing a table including a plurality of extracted terms. In this case, the extracted terms listed in  FIG. 4  are obtained by executing a segmentation process with regard to the source code of a news webpage published on Yahoo!News Taiwan (Title: “   ” (The high proportion of dispatch workers, the Ministry of Education was scolded, pinyin: pai qian gong bi li guo gao jiao yu bu ai hong), dated Oct. 25, 2013). In some embodiments, after retrieving the extracted terms  122 , the retrieved extracted terms  122  are then stored in the database group  16 . Herein, the database group  16  can be either one or both of a local storage device and a remote (cloud) storage device. 
     Referring to  FIGS. 1 and 2  again, the term mapping unit  14  retrieves the extracted term  122  from the database group  16  and then compares the extracted term  122  with the second text files  222  of the second server  22  (step S 26 ). Next, the step S 28  is to check whether the content of at least one second text file  222  of the second server  22  contains the extracted term  122 . If yes, the step S 30  is executed to execute a generalized term extraction procedure, a synonym extraction procedure, or a homonym extraction procedure so as to correspondingly generate generalized term information, synonym information or homonym information. After generating the generalized term, synonym or homonym information, the generated information can be stored in the database group  16 . To be noted, the generated information can be stored in the database storing the extracted term or a different database. In addition, when the user interface unit  18  receives a query term  182 , which is inputted by a user, the step S 32  is executed to provide generalized term, synonym or homonym information according to the query term  182 . 
       FIG. 5  is a flow chart showing the details of the step S 30  of  FIG. 2 , which is to execute a generalized term extraction procedure. Referring to  FIG. 5 , when the step S 28  of  FIG. 2  determines the content of one of the second text files contains the extracted term, the step S 502  of  FIG. 5  is executed to determine whether the extracted term contains a number in a Chinese word. Then, if the step S 502  determines that the extracted term contains a number in a Chinese word, the step S 506  is executed to search a location of the extracted term in the second text file and then execute the generalized term extraction procedure. 
     Afterwards, the step S 508  is executed to determine whether at least one specific character exists behind the extracted term. In this embodiment, the specific character is, for example, “ ” (a Chinese back sloping comma), “ ” (or, pinyin: huo), “ ” (and, pinyin: yi ji), or “ ” (and, pinyin: he). If the step S 508  determines that at least one of the above-mentioned specific characters exists behind the extracted term of the second text file, the step S 510  is executed to determine whether the total number of the specific characters behind the extracted term matches the number in the Chinese word. To be noted, to determine whether the total number of the specific characters matches the number in the Chinese word is not restricted to determine whether the total number of the specific characters (Chinese back sloping commas) “is equal to” the number in the Chinese word. In general, the total number of the specific characters (the consecutive Chinese back sloping commas in the text content) is equal to the number in the Chinese word minus one. This embodiment will be further described in details in the following description. 
     If the step S 510  determines that the total number of the specific characters matches the number in the Chinese word, the step S 512  is executed to extract all the terms in front of and behind the specific characters (the consecutive Chinese back sloping commas) as the generalized term information. 
     For example, when the extracted term  122  is “ ” (army, pinyin: san jun), the term mapping unit  14  determines the extracted term  122  contains a number in a Chinese word, “ ” (three, pinyin: san). Accordingly, the term mapping unit  14  starts to execute a generalized term extraction procedure so as to search the Wikipedia server and find out the webpages containing and/or related to the term “ ”. Then, this procedure is to search the location of the term “ ” from the searched webpage, and then determine whether at least one Chinese back sloping comma exists behind the term “ ”. 
     In practice, the searched webpage containing the term “ ” (the matched second text file  222 ) includes the following description: “     ” (army generally includes a senior army, an intermediate army and a lower army; pinyin: san jun chang cheng wei shang jun zhong jun xia jun). 
     In this case, the number of the Chinese back sloping comma “ ” existed behind the term “ ” is 2 (equal to 3−1). Accordingly, it is determined that the total number of the at least one Chinese back sloping comma (2) behind the extracted term matches the number in the Chinese word (3). As a result, the term mapping unit  14  extracts the terms (“ ”, “ ” and “ ”) in front of and behind the Chinese back sloping commas (“ ”) as the generalized term information and then stores the extracted generalized term information in the database group  16 . 
     Referring to  FIG. 1  again, after receiving the query term  182  inputted by the user, the user interface unit  18  determines whether the query term  182  matches the extracted term  122  of the database group  16 . In this case, if the user inputs the term “ ” in the searching page  60  as the query term  182 , the user interface unit  18  will show the above-mentioned generalized term information as shown in  FIG. 6A . In  FIG. 6A , the term  62  is the query term inputted by the user, and the terms  64   a ,  64   b ,  64   c  and  64   d  are the above-mentioned generalized term information. Accordingly, the user can quickly search the correct information with respect to the query term. 
     In one embodiment of the invention, the user interface unit  18  is a webpage browser such as Chrome, Firefox, Safari, IE or the likes. However, in other embodiments, the system for obtaining information can be a plug-in module or software cooperating with the above-mentioned webpage browser. 
     Please referring to  FIG. 5 , if the step S 502  determines that the extracted term does not contain a number in a Chinese word, the step S 504  is to execute another procedure such as the synonym extraction procedure or the homonym extraction procedure.  FIG. 7  is a flow chart showing the steps of executing a synonym extraction procedure according to a first embodiment of the invention. As shown in  FIG. 7 , when the step S 28  of  FIG. 2  determines that the text content of one of the second text files contains the extracted term and the step S 502  of  FIG. 5  determines that the extracted term does not contain a number in a Chinese word, the step S 702  is executed to search a location of the extracted term in the second text file. Then, the step S 704  is to extract the first term in the paragraph containing the extracted term as the synonym (synonym information). 
     For example, when the extracted term  122  of  FIG. 1  is “ ” (NYU, pinyin: yun ke da), the term mapping unit  14  searches the second server  22  (e.g. a Wikipedia server) to obtain a qualified second text file  222 , which is a webpage containing the following description: “       . . . ” (National Yunlin University of Science and Technology, which is also called for short as NYU or Yun Tech, and formerly known as National Yunlin Technical College; pinyin: guo li yun lin ke ji da xue, jian cheng yun ke da huo yun ke. Qian shen wei guo li yun lin ji shu xue yuan.) 
     Then, the term mapping unit  14  extracts the first term of the paragraph (as the above Chinese paragraph) containing the extracted term  122  as the synonym information. In this case, the term “ ” (National Yunlin University of Science  and Technology; pinyin: guo li yun lin ke ji da xue) is extracted as the synonym information. 
       FIG. 8  is a flow chart showing the steps of executing a synonym extraction procedure according to a second embodiment of the invention. Referring to  FIG. 8 , in the synonym extraction procedure of this embodiment, the step S 802  is executed to search a location of the extracted term  122  in the matched second text file  222 . In addition, since the term description and the abbreviation(s) thereof are shown in boldfaced words. Accordingly, after retrieving the location of the extracted term, the step S 804  is executed to extract the boldfaced words in the paragraph containing the extracted term as the synonym information. In the above example, the extracted term  122  is “ ” (NYU, pinyin: yun ke da), so that the term mapping unit  14  extracts the boldfaced words in the paragraph containing the extracted term, including the terms “ ” (National Yunlin University of Science and Technology; pinyin: guo li yun lin ke ji da xue) and “ ” (Yun Tech, pinyin: yun ke). As a result, the term mapping unit  14  will extract a combination of these boldfaced words as the synonym information. 
     In other embodiments, the synonym extraction procedure may further include a step of: extracting a term located at a specific position in the matched second text file as the synonym information according to an editing rule of the second text file. 
       FIG. 9  is a flow chart showing the steps of executing a synonym extraction procedure according to a third embodiment of the invention. In Wikipedia Taiwan, the term of an organization (in Chinese) is usually followed by the English translation thereof (some terms have no English translations) and the abbreviation of the organization. In this case, the followed abbreviation can be used as the synonym information. In this embodiment, the term mapping unit  14  firstly executes the step S 902  to determine whether the extracted term  122  is or is contained in the title of the matched second text file  222 . If yes, the step S 904  is executed to extract the followed terms in the title as the synonym information. On the contrary, if not, the step S 906  is executed to perform other synonym extraction procedures. 
     For example, when the extracted term  122  is “ ” (National Yunlin University of Science and Technology; pinyin: guo li yun lin ke ji da xue), the term mapping unit  14  can find the matched second text file  222  as shown above and determine the extracted term  122  is the title of the matched second text file  222 . Accordingly, the term mapping unit  14  extracts the following term, such as “   ” (NYU, pinyin: yun ke da) and “ ” (Yun Tech, pinyin: yun ke), as the synonym information. 
     In addition, after examining the editing structure of Wikipedia, it is discovered that the Wikipedia uses Infobox to record a lot of structural information (as shown in  FIG. 10A ). Accordingly, the synonym extraction procedure can be performed as shown in  FIG. 10B . Referring to  FIG. 10B , the step S 1004  is to retrieve the content in the Infobox (see  FIG. 10A ) of the second text file  222  (the related webpage). Then, the step S 1006  is executed to extract the information in the corresponding column of the Infobox as the synonym information. For example,  FIG. 10A  shows an Infobox  1000  of a webpage related to “ ” (National Taiwan University; pinyin: guo li tai wan da xue). In this embodiment, the term mapping unit  14  extracts the “nickname” column in the Infobox  1000  (the column labeled by the block  1002 ), which is “ ” (Azaleas Town; pinyin: dujuan hua cheng), as the synonym information. 
     The above embodiments disclose the steps of several synonym extraction procedures. This invention can execute one or the combination of the above mentioned embodiments to perform the synonym extraction procedure. In addition, those skilled persons in the art can execute other synonym extraction procedures without departing the spirit of the invention. 
     In addition, when the term mapping unit  14  determines that more than one second text file  222  contains the extracted term  122 , a homonym extraction procedure will be executed. In this embodiment, the term mapping unit  14  processes the contents of all matched second text files according to a term combination rule so as to generate the homonym information.  FIG. 11  is a flow chart showing the steps of executing a homonym extraction procedure according to a preferred embodiment of the invention. Referring to  FIG. 11 , when the term mapping unit  14  determines that more than one second text file  222  contains the extracted term  122 , the step S 1102  is executed to determine whether the paragraph of each matched second text file  222  containing the extracted term  122  also contains a restricted term for restricting the extracted term  122 . If there is no restricted term exist, the step S 1104  is executed to add the extracted term  122  into the homonym information. 
     On the contrary, if the paragraph of the matched second text file  222  containing the extracted term  122  also contains a restricted term, the step S 1106  is executed to combine the restricted term and the extracted term  122  and add the combined term into the homonym information. 
     For example, when the extracted term  122  is “ ” (pinyin: xiao tian tian), the term mapping unit  14  searches the Wikipedia Taiwan server and finds out the webpage relating to a Japanese historical romance novel, manga, and anime series and the webpage relating to a Taiwanese performer. In the webpage containing the term “ ”, which relates to a Japanese historical romance novel, manga, and anime series, the paragraph containing the extracted term  122  does not include any restricted term. Accordingly, the term mapping unit  14  directly adds the term “   ” into the homonym information. Alternatively, if the preset restricted terms include “ ” (mganga; pinyin: man hua) or “ ” (anime (cartoon); pinyin: ka tong), the term mapping unit  14  can find corresponding restricted term in the paragraph. In this case, the term mapping unit  14  will add the term “ ” (manga Candy Candy; pinyin: man hua xiao tian tian) and/or “ ” (anime (cartoon) Candy Candy; pinyin: ka tong xiao tian tian) into the homonym information. 
     Similarly, if the restricted terms include “ ” (performer; pinyin: yi ren), the term mapping unit  14  can find this restricted term from the paragraph containing the extracted term  122  in the webpage relating the containing a Taiwanese performer. Accordingly, the term mapping unit  14  adds the term “ ” (performer; pinyin: yi ren xiao tian tian) into the homonym information. In this case, the homonym information contains the terms “ ” and “ ”, or the terms “ ” (and/or “ ”) and “ ”. 
       FIG. 6B  is a schematic diagram showing the searching result according to a second embodiment of the invention. Referring to  FIG. 1  and the step S 32  of  FIG. 2  in view of  FIG. 6B , when a user inputs the term “ ” in the searching page  60  as the query term  66 , the user interface unit  18  provides the synonym information  68   a  or  68   b . Of course, if there are multiple second text files  222  contain the query term  66 , the user interface unit  18  also provides the related synonym information as mentioned above. 
     In order to improve the correction of the searching result, some embodiments of the invention may provide an agreement score mechanism for achieving the user interaction purpose.  FIG. 12A  is a schematic diagram showing a displayed screen of the agreement scores according to a preferred embodiment of the invention. In view of  FIG. 12A , the user interface unit  18  provides an agreement score webpage  70  for user interaction. In the following embodiment, the query term is “ ” (army, pinyin: san jun). In this case, the agreement score webpage  70  lists  all terms of the corresponding generalized term information, such as the terms  64   a ,  64   b ,  64   c  and  64   d . Accordingly, the agreement scores of the terms will be continuously recalculated based on new inputs. When the agreement score of one of these terms (e.g. the term  64   a ) is lower than a threshold value, the term  64   a  will be removed from the generalized term list. This operation can also be applied to the above mentioned synonym information and homonym information, so the detailed descriptions thereof will be omitted. 
     Besides, some embodiments of the invention allow the user to add new terms into the generalized term, synonym and homonym information (list).  FIG. 12B  is a schematic diagram showing a displayed screen of adding terms according to a preferred embodiment of the invention. Referring to  FIG. 12B , in an adding term webpage  72 , the suggested words  64   e  (“ ” (infantry, cavalry, navy; pinyin: bu jun, ma jun, shui jun)) are extracted and added to the generalized term information corresponding to the query term “ ”. Accordingly, the generalized term information corresponding to the query term “ ” further contains the term  64   e  (as shown in  FIG. 12C ). Similarly, the added term  64   e  can be evaluated by users to determine whether it should be remained in or removed from the generalized term information. In brief, the contents of the generalized term, synonym and homonym information can not only be collected from the second text files  222  of the second server  22  but also be edited by the users, thereby improving the accuracy of the information and adaptation of the change. 
     In summary, this invention can retrieve the extracted term from the first server and compare the extracted term with the second text files of the second server so as to obtain the desired generalized term, synonym and homonym information. Accordingly, this invention can improve the searching efficiency, thereby providing correct information with respect to the query term(s). 
     Although the invention has been described with reference to specific embodiments, this description is not meant to be construed in a limited sense. Various modifications of the disclosed embodiments, as well as alternative embodiments, will be apparent to persons skilled in the art. It is, therefore, contemplated that the appended claims will cover all modifications that fall within the true scope of the invention.