私はいくつかのpdfファイルを持っています、pdfboxを使用してテキストに変換してテキストファイルに保存しました、今削除したいテキストファイルから
このような行ごとに有効なテキストを取得したい:
オントゲイン、プレーンテキストから抽出された複数の単語の概念用語からオントロジーを学習する方法を提案します。 OntoGainは、個別の処理層によって定義されたオントロジー学習プロセスに従います。単純な用語の抽出に基づいて、抽出された概念をクラスタリングすることにより、概念階層が形成されます。派生した用語分類は、非分類関係で強化されます。各層を実装するために、いくつかの最新の方法が検討されています。 OntoGainは、複数の単語または複合用語が単純な単一の単語用語よりも堅実で独特のセマンティクスを備えているため、複数の単語用語の概念に基づいています。用語分類を構築するために、階層的クラスタリング手法と形式的概念分析(FCA)アルゴリズムを選択しました。さらに、非分類関係を明らかにするために、相関ルールアルゴリズムが適用されます。リレーションの概念間で最も適切な一般化レベルを実行しようとするメソッドも実装されます。概念実証を示すために、システムのプロトタイプが実装されています。 OntoGainでは、Jena Semantic Web Frame-work1を使用して、派生したオントロジーをOWLに変換できます。 OntoGainは、医学とコンピューターの2つの別個のデータソースに適用され、その結果は、最先端のオントロジー学習方法であるText2Ontoによって得られた同様の結果と比較されます。 11.5 CCD1.1の結果の分析は、OntoGainがText2Ontoよりも正確な概念を抽出し、より選択的で少ないが合理的な概念を抽出するという点で優れていることを示しています。
どうすればこれを達成できますか?
pdfbox を使用すると、これを実現できます
例:
public static void main(String args[]) {
PDFParser parser = null;
PDDocument pdDoc = null;
COSDocument cosDoc = null;
PDFTextStripper pdfStripper;
String parsedText;
String fileName = "E:\\Files\\Small Files\\PDF\\JDBC.pdf";
File file = new File(fileName);
try {
parser = new PDFParser(new FileInputStream(file));
parser.parse();
cosDoc = parser.getDocument();
pdfStripper = new PDFTextStripper();
pdDoc = new PDDocument(cosDoc);
parsedText = pdfStripper.getText(pdDoc);
System.out.println(parsedText.replaceAll("[^A-Za-z0-9. ]+", ""));
} catch (Exception e) {
e.printStackTrace();
try {
if (cosDoc != null)
cosDoc.close();
if (pdDoc != null)
pdDoc.close();
} catch (Exception e1) {
e1.printStackTrace();
}
}
}
こんにちは、 Apache Tikaを使用してpdfファイルを抽出できます
例は:です
import Java.io.IOException;
import Java.io.InputStream;
import Java.util.HashMap;
import Java.util.Map;
import org.Apache.http.HttpEntity;
import org.Apache.http.HttpResponse;
import org.Apache.http.client.methods.HttpGet;
import org.Apache.http.impl.client.DefaultHttpClient;
import org.Apache.tika.metadata.Metadata;
import org.Apache.tika.metadata.TikaCoreProperties;
import org.Apache.tika.parser.AutoDetectParser;
import org.Apache.tika.parser.ParseContext;
import org.Apache.tika.sax.BodyContentHandler;
public class WebPagePdfExtractor {
public Map<String, Object> processRecord(String url) {
DefaultHttpClient httpclient = new DefaultHttpClient();
Map<String, Object> map = new HashMap<String, Object>();
try {
HttpGet httpGet = new HttpGet(url);
HttpResponse response = httpclient.execute(httpGet);
HttpEntity entity = response.getEntity();
InputStream input = null;
if (entity != null) {
try {
input = entity.getContent();
BodyContentHandler handler = new BodyContentHandler();
Metadata metadata = new Metadata();
AutoDetectParser parser = new AutoDetectParser();
ParseContext parseContext = new ParseContext();
parser.parse(input, handler, metadata, parseContext);
map.put("text", handler.toString().replaceAll("\n|\r|\t", " "));
map.put("title", metadata.get(TikaCoreProperties.TITLE));
map.put("pageCount", metadata.get("xmpTPg:NPages"));
map.put("status_code", response.getStatusLine().getStatusCode() + "");
} catch (Exception e) {
e.printStackTrace();
} finally {
if (input != null) {
try {
input.close();
} catch (IOException e) {
e.printStackTrace();
}
}
}
}
} catch (Exception exception) {
exception.printStackTrace();
}
return map;
}
public static void main(String arg[]) {
WebPagePdfExtractor webPagePdfExtractor = new WebPagePdfExtractor();
Map<String, Object> extractedMap = webPagePdfExtractor.processRecord("http://math.about.com/library/q20.pdf");
System.out.println(extractedMap.get("text"));
}
}
iText を使用して、そのようなことを行うことができます
//iText imports
import com.itextpdf.text.pdf.PdfReader;
import com.itextpdf.text.pdf.parser.PdfTextExtractor;
例えば:
try {
PdfReader reader = new PdfReader(INPUTFILE);
int n = reader.getNumberOfPages();
String str=PdfTextExtractor.getTextFromPage(reader, 2); //Extracting the content from a particular page.
System.out.println(str);
reader.close();
} catch (Exception e) {
System.out.println(e);
}
別の
try {
PdfReader reader = new PdfReader("c:/temp/test.pdf");
System.out.println("This PDF has "+reader.getNumberOfPages()+" pages.");
String page = PdfTextExtractor.getTextFromPage(reader, 2);
System.out.println("Page Content:\n\n"+page+"\n\n");
System.out.println("Is this document tampered: "+reader.isTampered());
System.out.println("Is this document encrypted: "+reader.isEncrypted());
} catch (IOException e) {
e.printStackTrace();
}
上記の例ではテキストのみを抽出できますが、ハイパーリンク、箇条書き、見出しと数字を削除するには、さらにいくつか行う必要があります。
ローカルマシンまたはBase64エンコード文字列のPDFファイルからすべてのキーワードを抽出:
import org.Apache.commons.codec.binary.Base64;
import org.Apache.pdfbox.pdmodel.PDDocument;
import org.Apache.pdfbox.text.PDFTextStripper;
import Java.io.File;
import Java.io.FileInputStream;
import Java.io.FileNotFoundException;
import Java.io.IOException;
import Java.util.HashMap;
import Java.util.Map;
public class WebPagePdfExtractor {
public static void main(String arg[]) {
WebPagePdfExtractor webPagePdfExtractor = new WebPagePdfExtractor();
System.out.println("From file: " + webPagePdfExtractor.processRecord(createByteArray()).get("text"));
System.out.println("From string: " + webPagePdfExtractor.processRecord(getArrayFromBase64EncodedString()).get("text"));
}
public Map<String, Object> processRecord(byte[] byteArray) {
Map<String, Object> map = new HashMap<>();
try {
PDFTextStripper stripper = new PDFTextStripper();
stripper.setSortByPosition(false);
stripper.setShouldSeparateByBeads(true);
PDDocument document = PDDocument.load(byteArray);
String text = stripper.getText(document);
map.put("text", text.replaceAll("\n|\r|\t", " "));
} catch (Exception exception) {
exception.printStackTrace();
}
return map;
}
private static byte[] getArrayFromBase64EncodedString() {
String encodedContent = "data:application/pdf;base64,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" +
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String content = encodedContent.substring("data:application/pdf;base64," .length());
return Base64.decodeBase64(content);
}
public static byte[] createByteArray() {
String pathToBinaryData = "/bla-bla/src/main/resources/small.pdf";
File file = new File(pathToBinaryData);
if (!file.exists()) {
System.out.println(" could not be found in folder " + pathToBinaryData);
return null;
}
FileInputStream fin = null;
try {
fin = new FileInputStream(file);
} catch (FileNotFoundException e) {
e.printStackTrace();
}
byte fileContent[] = new byte[(int) file.length()];
try {
fin.read(fileContent);
} catch (IOException e) {
e.printStackTrace();
}
return fileContent;
}
}