This node analyses documents and extracts relevant keywords
using the graph-based approach described in
"KeyGraph: Automatic Indexing by Co-occurrence Graph based on
Building Connstruction Metaphor" by Yukio Ohsawa.
First, a predetermined amount of terms are selected based on their
frequency (high frequency set, HF) and added as the initial nodes of
the graph.
The association strength between each of these terms is then
calculated using the following scoring method: assoc(term1, term2) =
min(occurrence frequency of term1, occurrence frequency of term2)
summed for every sentence in the document.
The top |HF|-1 associations are inserted into the graph as edges.
If an edge between two terms is the only path that connects them, it
is pruned.
The graph's connected subgraphs are then extracted and considered as
"concept" clusters.
A new batch of terms is added based on their key score, which is the
conditional probability that a term will be used if the author has
all the concepts (clusters) in mind (P(UNION(w|g)) where t is the
term and the union is done over every cluster g of the set of clusters.
Each of these new terms is then linked to every cluster using the
strongest scoring edge amongst the possible ones.
Finally, all the terms in the graph are rated based on this formula:
score(t) = summation over every edge connecting t and other terms (w),
summation over every sentences, min(freq(t), freq(w)).
Setting the console's output level to DEBUG will make this node
display the contents of the clusters after the pruning phase.
terms.
Options
Popular Predecessors
Bag of Words Creator11 %Strings To Document6 %Stop Word Filter6 %- Partitioning3 %
- Punctuation Erasure2 %
- TF2 %
Row Filter (deprecated)2 %- PDF Parser2 %
- Tag Filter2 %
File Reader1 %- Rule Engine1 %
- Snowball Stemmer1 %
- String Manipulation1 %
- GroupBy1 %
- Case Converter1 %
- Stanford Tagger1 %
- Document Data Assigner1 %
- Strings to Document1 %
- Statistics1 %
Joiner1 %- Keygraph Keyword Extractor1 %
- Dictionary Filter1 %
- Stanford Lemmatizer1 %
- Stop Word Filter1 %
- Excel Reader1 %
- IDF< 1 %
- Chi-Square Keyword Extractor< 1 %
- Kuhlen Stemmer< 1 %
- N Chars Filter< 1 %
- Porter Stemmer< 1 %
- Replacer< 1 %
- Tika Parser< 1 %
- Bag Of Words Creator< 1 %
- Duplicate Row Filter< 1 %
POS tagger< 1 %- DB Reader< 1 %
- Number Filter< 1 %
- Word Parser< 1 %
OpenNLP NE tagger< 1 %Stanford tagger< 1 %- Sentence Extractor< 1 %
- Twitter Search (legacy)< 1 %
- Abner Tagger< 1 %
- Dictionary Tagger< 1 %
- StanfordNLP NE Tagger< 1 %
- Chunk Loop Start< 1 %
Concatenate (Optional in)< 1 %- Column Filter< 1 %
Column Rename< 1 %- DF< 1 %
- Frequency Filter< 1 %
- Topic Extractor (Parallel LDA)< 1 %
- Category to Class< 1 %
- String Matcher< 1 %
- PubMed Document Parser< 1 %
- k-Means< 1 %
- Dictionary Replacer< 1 %
- Regex Substring< 1 %
- Cell Splitter< 1 %
IF Switch (Flow Variable Value)< 1 %Table Reader< 1 %- Java Snippet< 1 %
- Concatenate< 1 %
- Reference Row Filter< 1 %
- Reference Row Splitter< 1 %
- Table Transposer< 1 %
- Color Manager< 1 %
XLS Reader< 1 %Excel Reader (XLS)< 1 %- Term Co-Occurrence Counter< 1 %
- NGram Creator< 1 %
- Tag Stripper< 1 %
RSS Feed Reader< 1 %Wildcard tagger< 1 %- Document Vector< 1 %
- Tags to String< 1 %
- Parameter Optimization Loop Start< 1 %
- XPath< 1 %
- Case Converter< 1 %
- Term Document Entropy< 1 %
- Dictionary Replacer (File-based)< 1 %
- Term Vector< 1 %
- Scorer< 1 %
- Meta Info Inserter< 1 %
- Scatter Plot (JavaScript)< 1 %
Table Row to Variable< 1 %CSV Reader< 1 %Database Connection Table Reader< 1 %List Files< 1 %- Table Creator< 1 %
Counting Loop Start< 1 %Row Splitter (deprecated)< 1 %- Sorter< 1 %
- String Replacer< 1 %
- Rule-based Row Splitter< 1 %
- Vocabulary Extractor (legacy)< 1 %
POS Filter< 1 %- Document Grabber< 1 %
- Flat File Document Parser< 1 %
- POS Tagger< 1 %
- Document Data Extractor< 1 %
- String to Term< 1 %
- Term to String< 1 %
- N-Gram Extractor< 1 %
- HTML Parser< 1 %
- Load Text Files< 1 %
- Extract URI Info< 1 %
- String to URI< 1 %
Table Row To Variable Loop Start< 1 %Database Reader< 1 %Simple File Reader< 1 %Line Reader< 1 %- Loop End (Column Append)< 1 %
Generic Loop Start< 1 %- Group Loop Start< 1 %
- Bootstrap Sampling< 1 %
Cell Splitter< 1 %- Table Validator< 1 %
- Nominal Value Row Splitter< 1 %
- Missing Value< 1 %
- Row Sampling< 1 %
- Set Operator< 1 %
String Replace (Dictionary)< 1 %- Cache< 1 %
- Math Formula< 1 %
- Geo-Coordinate Row Filter< 1 %
Excel Reader (XLS)< 1 %- Markup Tag Filter< 1 %
- Tika Language Detector< 1 %
- Diacritic Remover< 1 %
- Modifiable Term Filter< 1 %
- RegEx Filter< 1 %
- Dml Document Parser< 1 %
Abner tagger< 1 %Dictionary tagger< 1 %- Wildcard Tagger< 1 %
- OpenNLP NE Tagger< 1 %
Document vector< 1 %- Unique Term Extractor< 1 %
- Tagged Document Viewer< 1 %
- Tag Cloud (JavaScript)< 1 %
- Corpus Creator< 1 %
- AP Calculator< 1 %
- URL Resolver< 1 %
- HTML Node to Text< 1 %
- CSV Reader< 1 %
- File Reader (Complex Format)< 1 %
- Column Aggregator< 1 %
- Column Resorter< 1 %
- One to Many< 1 %
- RowID< 1 %
- Term Neighborhood Extractor< 1 %
Views
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Workflows
01_Sentiment_Analysis_ML_ApproachKNIME Hub- 01_Sentiment_Analysis_ML_ApproachKNIME Hub
- 01_Topic_Detection ClusteringKNIME Hub
- 01_Topic_Detection ClusteringKNIME Hub
- 02_Num_Keywords_Sentiment_Analysis_MLKNIME Hub
- Show all 21 workflows
Links
- No links available
Developers
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