Abstract: A nano-FET and a method of forming is provided. In some embodiments, a nano-FET includes an epitaxial source/drain region contacting ends of a first nanostructure and a second nanostructure. The epitaxial source/drain region may include a first semiconductor material layer of a first semiconductor material, such that the first semiconductor material layer includes a first segment contacting the first nanostructure and a second segment contacting the second nanostructure, wherein the first segment is separated from the second segment. A second semiconductor material layer is formed over the first segment and the second segment. The second semiconductor material layer may include a second semiconductor material having a higher concentration of dopants of a first conductivity type than the first semiconductor material layer. The second semiconductor material layer may have a lower concentration percentage of silicon than the first semiconductor material layer.

Abstract: A method for analyzing a technology document is adapted to a technology document and includes providing a technology structure network. The technology structure network has several technology category groups representing several technology categories correspondingly. Each technology category group is a technology hierarchical class having several technology levels from top to bottom and each technology level has at least one technology node. Then, statistics for terms are calculated to analyze a content of the technology document so as to find out at lest one particular term. Next, a co-occurrence correlation is established between each of the particular terms and each of the technology nodes in the technology structure network. Then, according to the correlations, a technical field of the technology document is identified.

Abstract: A method for searching data from a database is provided. The method comprises steps of determining a data set from the database according to a searching target. The data set includes several documents related to the searching target. Then, a content of each of the documents is analyzed to generate a queue of term frequency. Thereafter, according to the queue of the term frequency, a low frequency keyword candidate list is generated. Furthermore, according to the low frequency keyword candidate list and the queue of the term frequency, an effective keyword list is generated. Then, according to the effective keyword list, a document searching result is determined and the document searching result lists several documents in relation to the searching target in the database.