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In the age of Internet, with the online information explosive growth, people want to find information we need in the cyberworld fleetly and exactly. The information retrieval method based on the keyword or the simple logic-combination of the keywords has been unable to meet the people's need of information getting to
desirable. In this paper, some existing achievements are investigated firstly. Then our current technique on web information extraction is discussed in detail. In our approach, rules and patterns are extracted from sample pages through training process, with human involvements. We use both keywords and regular expressions to
found will be categorized into three groups: Positive link, Negative link and Neutral link. The objective is to identify whether the link is likely pointing into relevant documents or not. In addition, we also utilize keywords related financial domain to recognize a relevant document. Based on our experiments, the value of
order to collect and index only related Web documents. As requests can be insufficient to express sensitive and specific needs, the user's information needs are specified using user's interests represented by DBPedia resources [1] and keywords, both extracted from Web pages provided by the user. A series of experiments
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.