to support the new time parser and search functions in YaCy a high
precision detection of date and time on the day is necessary. That
requires that the time zone of the document content and the time zone of
the user, doing a search, is detected. The time zone of the search
request is done automatically using the browsers time zone offset which
is delivered to the search request automatically and invisible to the
user. The time zone for the content of web pages cannot be detected
automatically and must be an attribute of crawl starts. The advanced
crawl start now provides an input field to set the time zone in minutes
as an offset number. All parsers must get a time zone offset passed, so
this required the change of the parser java api. A lot of other changes
had been made which corrects the wrong handling of dates in YaCy which
was to add a correction based on the time zone of the server. Now no
correction is added and all dates in YaCy are UTC/GMT time zone, a
normalized time zone for all peers.
given css class and extends a given vocabulary with a term consisting
with the text content of the html class tag. Additionally, the term is
included into the semantic facet of the document. This allows the
creation of faceted search to documents without the pre-creation of
vocabularies; instead, the vocabulary is created on-the-fly, possibly
for use in other crawls. If any of the term scraping for a specific
vocabulary is successful on a document, this vocabulary is excluded for
auto-annotation on the page.
To use this feature, do the following:
- create a vocabulary on /Vocabulary_p.html (if not existent)
- in /CrawlStartExpert.html you will now see the vocabularies as column
in a table. The second column provides text fields where you can name
the class of html entities where the literal of the corresponding
vocabulary shall be scraped out
- when doing a search, you will see the content of the scraped fields in
a navigation facet for the given vocabulary
attribute in the <a> tag for each crawl. This introduces a lot of
changes because it extends the usage of the AnchorURL Object type which
now also has a different toString method that the underlying
DigestURL.toString. It is therefore not advised to use .toString at all
for urls, just just toNormalform(false) instead.
for anchor attributes.
- this caused that large portions of the parser code had to be adopted
as well
- added a counter target_order_i for anchor links in webgraph
computation
all unique links! This made it necessary, that a large portion of the
parser and link processing classes must be adopted to carry a different
type of link collection which carry a property attribute which are
attached to web anchors.
- introduction of a new URL class, AnchorURL
- the other url classes, DigestURI and MultiProtocolURI had been renamed
and refactored to fit into a new document package schema, document.id
- cleanup of net.yacy.cora.document package and refactoring
html meta fields to get a correct (or: better) date timestamp. The
http:last-modified mostly does not work because it is set to the current
date from most CMS.
- use ordered list to use preferred parser for mime/extension first (relates to html, rdfa, argument parser)
- harmonize xhtml extension config for the 3 html base parsers
note: stream.close is done by caller (Textparser.parseSource)
- removed unnecessary reset in AugmentParser
- added stream.mark in tdfatripleimpl. to make stream.reset work here
-- for some documents genericParser grabs document instead of specific available parser due to unordered pick of 1st to try parser
(like .ps .rdf files and other)
- remove redundant file extension registration
jdk-based logger tend to block
at java.util.logging.Logger.log(Logger.java:476) in concurrent
environments. This makes logging a main performance issue. To overcome
this problem, this is a add-on to jdk logging to put log entries on a
concurrent message queue and log the messages one by one using a
separate process.
- FTPClient uses the concurrent logging instead of the log4j logger
title_count_i, title_chars_val, title_words_val
description_count_i, description_chars_val, description_words_val
- added many asserts to ensure data type correctness from YaCy to Solr
and vice versa
- made many fixes according to new findings from these asserts (!)
of the major CPU users during snippet verification. The class was not
efficient for two reasons:
- it used a too complex input stream; generated from sources and UTF8
byte-conversions. The BufferedReader applied a strong overhead.
- to feed data into the SentenceReader, multiple toString/getBytes had
been applied until a buffered Reader from an input stream was possible.
These superfluous conversions had been removed.
- the best source for the Sentence Reader is a String. Therefore the
production of Strings had been forced inside the Document class.
later
- added abstract add, delete, get methods in the triplestore
- added generation of triples after auto-annotation
- migrated all MultiProtocolURI objects to DigestURI in the parser since
the url hash is needed as subject value in the triples in the triple
store