Розробка прототипу інтерфейсу користувача інформаційної системи

For intellectual activity in the time of information explosion, it is necessary to explore a lot of documents obtained from open sources of the Internet. The object of research is the interface and structure of the information system. This system allows to reduce the processed information flow by filtering documents. The filtration is based on the documents set clustering. This method is seldom used due to the complexity of the user interface.To solve this problem, it is proposed to use the mind map view for visualizing the clustering results. The cluster hierarchy automatically creates the initial graph of the map nodes. The binary graph of the clustering results will automatically transform to the n-ary graph tree. The n is no more than the Yngve-Miller's number and should be determined by the user. The user also controls the mapping of clusters to the mind map, using SQL-queries.The structure of the information system is determined. This system uses free software solutions as its integral parts. Neural network subsystem is required to adapt to the specific user needs.A prototype of the mind map user interface is developed. It is made in JavaScript and is represented as a web page. A list of the main use cases for implementation in the MVP (the minimum viable product) is given.Предложена структура информационной системы для уменьшения информационной перегрузки пользователя при работе с большим числом источников документов из интернет. Дан краткий список пользовательских историй. Получение документов происходит с помощью RSS-каналов. Интерфейс системы выполнен как интеллектуальная карта (mindmap). Выборка документов для узлов карты выполняется на основе правил, записанных на SQL-подобном языке запросов.Запропоновано структуру інформаційної системи для зменшення інформаційного перевантаження користувача при роботі з великим числом джерел документів з інтернет. Дан короткий список призначених для користувача історій. Отримання документів відбувається за допомогою RSS-каналів. Інтерфейс системи виконаний як інтелектуальна карта (mindmap). Вибірка документів для вузлів карти виконується на основі правил, записаних на SQL-подібній мові запитів

Web document clustering using a hybrid neural network

The list of documents returned by Internet search engines in response to a query these days can be quite overwhelming. There is an increasing need for organising this information and presenting it in a more compact and efficient manner. This paper describes a method developed for the automatic clustering of World Wide Web documents, according to their relevance to the user’s information needs, by using a hybrid neural network. The objective is to reduce the time and effort the user has to spend to find the information sought after. Clustering documents by features representative of their contents—in this case, key words and phrases—increases the effectiveness and efficiency of the search process. It is shown that a two-dimensional visual presentation of information on retrieved documents, instead of the traditional linear listing, can create a more user-friendly interface between a search engine and the user