Abstract: A package structure is provided. The package structure includes an encapsulant and an interposer. The encapsulant has a top surface and a bottom surface opposite to the top surface. The interposer is encapsulated by the encapsulant. The interposer includes a main body, an interconnector, and a stop layer. The main body has a first surface and a second surface opposite to the first surface. The interconnector is disposed on the first surface and exposed from the top surface of the encapsulant. The stop layer is on the second surface, wherein a bottom surface of the stop layer is lower than the second surface.

Abstract: A package structure is provided. The package structure includes an encapsulant and an interposer. The encapsulant has a top surface and a bottom surface opposite to the top surface. The interposer is encapsulated by the encapsulant. The interposer includes a main body, an interconnector, and a stop layer. The main body has a first surface and a second surface opposite to the first surface. The interconnector is disposed on the first surface and exposed from the top surface of the encapsulant. The stop layer is on the second surface, wherein a bottom surface of the stop layer is lower than the second surface.

Abstract: A substrate structure and a semiconductor package structure are provided. The substrate structure includes a first dielectric layer, a pad and a conductive structure. The first dielectric layer has a first surface and a second surface opposite to the first surface. The pad is adjacent to the first surface and at least partially embedded in the first dielectric layer. The first dielectric layer has an opening exposing the pad, and a width of the opening is less than a width of the pad. The conductive structure is disposed on the pad and composed of a first portion outside the opening of the first dielectric layer and a second portion embedded in the opening of the first dielectric layer. The first portion has an aspect ratio exceeding 1.375.

Abstract: A substrate structure and a semiconductor package structure are provided. The substrate structure includes a first dielectric layer, a pad and a conductive structure. The first dielectric layer has a first surface and a second surface opposite to the first surface. The pad is adjacent to the first surface and at least partially embedded in the first dielectric layer. The first dielectric layer has an opening exposing the pad, and a width of the opening is less than a width of the pad. The conductive structure is disposed on the pad and composed of a first portion outside the opening of the first dielectric layer and a second portion embedded in the opening of the first dielectric layer. The first portion has an aspect ratio exceeding 1.375.

Abstract: A semiconductor device package includes a first semiconductor device; a second semiconductor device; and a first redistribution layer disposed on the first semiconductor device and having a side wall defining an opening that exposes the first semiconductor device. The side wall of the first redistribution layer has an average surface roughness (Ra) in a range up to 2 micrometers (?m).

Abstract: A semiconductor device package includes a first semiconductor device; a second semiconductor device; and a first redistribution layer disposed on the first semiconductor device and having a side wall defining an opening that exposes the first semiconductor device. The side wall of the first redistribution layer has an average surface roughness (Ra) in a range up to 2 micrometers (?m).

Abstract: Systems, devices and methods are provided which relate to detecting a print command on a client computer, the print command reflecting an interest to print content of an electronic document, accessible by a client computer, as a hard copy printout. One method includes analyzing the electronic document content to determine its underlying subject matter, identifying commercial content relevant to the underlying subject matter, and creating and formatting a new, printable document that includes the electronic document content and the identified commercial content.

Abstract: A computer-implemented method of extracting key phrases from a document is disclosed comprising the steps of accessing a repository comprising linked subjects, the repository comprising first and second data structures representing the relationship between said subjects using different representation criteria; pruning the first data structure by removing links between subjects based on a further relationship between said subjects in the second data structure; matching phrases in said document to subjects in the pruned first data structure; further pruning the pruned first data structure by removing unmatched subjects that are not linked to matched subjects; determining a ranking for each matched subject; and selecting key phrases using the determined subject rankings. A computer program for implementing the steps of this method when executed on a computer is also disclosed.

Abstract: Semantically ranking content in a website (110) with a computerized ranking device (105) includes: parsing content from the website (110) into multiple autonomous content blocks (415-1 to 415-17) with the computerized ranking device (105) and assigning an importance ranking with said computerized ranking device (105) to each of the content blocks (415-1 to 415-17) based on a degree to which a substance of the content block (415-1 to 415-17) is relevant to one of a plurality of predefined categories.

Abstract: A system and method for automatically extracting meta data from unstructured electronic documents is disclosed. In one embodiment, the unstructured electronic document is converted into a plain text document. Further, a document header of the unstructured electronic document is extracted from the plain text document using a rule-based document header extractor, where the rule-based document header extractor may be based on a rule that includes determining a ratio of a number of words with their initial letters capitalized in a text line over a total number of words in the text line in the plain text document. Moreover, meta data is extracted from the extracted document header using a heuristic approach.

Abstract: A device for classifying a document comprises a module to generate a data tree structure and configured to assign terms to a first plurality of nodes of the data tree structure, where each of the first plurality of nodes is assigned a weight. In assigning the weights of the first plurality of nodes, a first generation of combinations of possible weights assignable as the weights of the first plurality of nodes is obtained, and a second generation of combinations of possible weights assignable as the weights of the first plurality of nodes is obtained by performing the genetic algorithms in the first generation of combinations of possible weights. The device determines whether the document is in a document class based at least the weights of the first plurality of nodes.

Abstract: A method of grouping a plurality of media content is provided. The method includes converting at least a portion of the media content into at least one document object model (“DOM”) using a processor. The DOM can include a plurality of block elements, each comprising at least one content object. The method includes apportioning the content objects into a relevant portion and an irrelevant portion and extracting a set of keywords, the set comprising at least one keyword, within the relevant portion of the content objects. The method includes apportioning the relevant portion of the content objects into a related portion and an unrelated portion using at least a portion of the set of keywords and grouping the related portion of the content to provide a group of related content.

Abstract: Semantically ranking content in a website (110) with a computerized ranking device (105) includes: parsing content from the website (110) into multiple autonomous content blocks (415-1 to 415-17) with the computerized ranking device (105) and assigning an importance ranking with said computerized ranking device (105) to each of the content blocks (415-1 to 415-17) based on a degree to which a substance of the content block (415-1 to 415-17) is relevant to one of a plurality of predefined categories.

Abstract: Presented is a method of extracting keywords. The method includes obtaining a corpus of documents, determining a first set of words that appear as keywords in a document present in the corpus of documents, determining a second set of words that appear in the corpus of documents but not necessarily appear as keywords in the document, and determining a final set of keywords for the document by combining the first set of words with the second set of words.

Abstract: A system and method for automatically extracting meta data from unstructured electronic documents is disclosed. In one embodiment, the unstructured electronic document is converted into a plain text document. Further, a document header of the unstructured electronic document is extracted from the plain text document using a rule-based document header extractor, where the rule-based document header extractor may be based on a rule that includes determining a ratio of a number of words with their initial letters capitalized in a text line over a total number of words in the text line in the plain text document. Moreover, meta data is extracted from the extracted document header using a heuristic approach.

Abstract: Disclosed is a method and apparatus for searching electronic documents. The 5 apparatus comprises first and second data repositories storing tags for representing content of an electronic document. The first data repository is adapted to store structured tags and their respective association with an electronic document, a structured tag comprising information representing its relationship to at least one other tag. The second data repository is adapted to 10 store free tags and their respective association with an electronic document, a free tag not comprising information representing its relationship to any other tags. Electronic documents can be searched by accessing the first and second data repositories, and matching a search query with one or more tags in the first and second data repositories. For each matched tag, an electronic document 15 associated with the tag can then be retrieved and a ranking for the electronic document determined based on attributes of the document and its associated tag.

Abstract: A computer-implemented method of extracting key phrases from a document is disclosed comprising the steps of accessing a repository comprising linked subjects, the repository comprising first and second data structures representing the relationship between said subjects using different representation criteria; pruning the first data structure by removing links between subjects based on a further relationship between said subjects in the second data structure; matching phrases in said document to subjects in the pruned first data structure; further pruning the pruned first data structure by removing unmatched subjects that are not linked to matched subjects; determining a ranking for each matched subject; and selecting key phrases using the determined subject rankings. A computer program for implementing the steps of this method when executed on a computer is also disclosed.

Abstract: A method of grouping a plurality of media content is provided. The method includes converting at least a portion of the media content into at least one document object model (“DOM”) using a processor. The DOM can include a plurality of block elements, each comprising at least one content object. The method includes apportioning the content objects into a relevant portion and an irrelevant portion and extracting a set of keywords, the set comprising at least one keyword, within the relevant portion of the content objects. The method includes apportioning the relevant portion of the content objects into a related portion and an unrelated portion using at least a portion of the set of keywords and grouping the related portion of the content to provide a group of related content.