# Development of Intellectual Web System for Morph Analyzing of Uzbek Words
## 5 Problems and Solution  
(1) Despite the fact that we made a significant effort in the framework of the research, our system has a few disadvantages. First of all, the system uses exception word sets during analyzing words; due to it is planned to add new words by experts, it is highly possible that we might not include some words, which could vitally important for certain users. For instance, our dictionaries of exception words will mostly contain words of scientific branch, while the quantity of words in such areas as literature or cooking will be noticeably less. So, cooks or writers may not be interested in our system. \begin{table}
\begin{tabular}{c c c} \hline \hline
**id** & **Input** & **Output** \\ \hline
1. & bahorgi & “bahor”: “Root word (n. spring)”, \\  & & “gi”: “Endings that form adjectives from nouns: \\  & & bahorgi (adj; spring)” \\  & & “kelin”: “root word (bride)”, \\
2. & kelinchak & “chak”: “this ending is used as an “affectionate” \\  & & “data”: “root word (father)”, \\
3. & dadamlar & “m”: “ auxiliary particle”, \\  & & “lar”: “ this ending is used as an affectionate, not as an plural ending” \\ \hline \hline \end{tabular}
\end{table} 
Table 14: Morphological analysis of words (words will not be stemmed, because they are stored in one of the exception word sets). Figure 3: Detailed scheme of working process. As for the solution of the problem, it might be emphasized that we will gradually expand the capacity of the exception word sets. Although, this will take a long time. (2) In the meanwhile, there is another problem of the language. Taking into account the fact that there are three families of dialects in the Uzbek language [18], some users might have made a mistake during the use of our API. The main point is that such dialects as Oguz, Kypchak, and Chagatay made a significant contribution to the formation of the modern Uzbek language. However, current official Uzbek language mostly belongs to Chagatay's dialect. Although, other groups of dialects are still being used among local people in different regions. Take, for example, in the west part of Uzbekistan (Khorezm region), people use the Oguz dialect of the Uzbek language (Khorezmian dialect [18]), while in the east part of the country, only the Chagatay dialect is used. Additionally, in the middle-north area of the state, people speak in the Kypchak dialect. In addition, the Khorezmian language was formed thanks to the influence of a wide variety of non-Turkic languages, such as Persian, Arabic, and others. So, assume that a user from the Khorezm region sent a word to the system in order to morphologically analyze it. That user will likely make a mistake during typing a word. For instance, in Khorezm, people say _vagi'rdi_, which means \"noise\", while in the Tashkent dialect (official Uzbek), people would say _shovqin_. Additionally as an additional example, the word \"ice\" in the Khorezmian dialect is spoken as _buz_ [bu:z], while in the other two dialects of the Uzbek language, it is spoken as _muz_. It should be noted that Khorezmian _buz_ in the official Uzbek means \"to destroy\". Although Oguz dialect's vocabulary has some differences compared with the other two dialects, native speakers of all dialects can understand each other by the context of their conversation. The only solution that we came up with is to create additional word sets in our system, which will be connected to the existing exception word sets by words themselves. So, it is supposed to be as follows (Figure 4):  
(3) Last, but not the least, let us imagine that the user during his interaction with our system sent a word that was written grammatically incorrectly. For instance, instead of _kelinchak_ (\"bride\"), the user typed _kalinchak_. Actually, in this case, our API is not able to recognize this word as _kelinchak_; however, we managed to find out solution! There is an algorithm that helps to analyze the string by comparing the user's word and words from the word's set, and this algorithm is called Levenshtein [19].