Assume a very large corpus of any inflective language. Does the following make sense? By applying LSA on such corpus, words with similar concepts converge together in vector space, thus inflected word forms reffering to the same concept should ideally be identical with their lemma in the space. With such assumption, any lemmatization or stemming of queries or corpus is not necessary. Or am i totally wrong?
Latent Semantic Analysis and Stemming
314 Views Asked by L D At
1
There are 1 best solutions below
Related Questions in NLP
- Seeking Python Libraries for Removing Extraneous Characters and Spaces in Text
- Clarification on T5 Model Pre-training Objective and Denoising Process
- The training accuracy and the validation accuracy curves are almost parallel to each other. Is the model overfitting?
- Give Bert an input and ask him to predict. In this input, can Bert apply the first word prediction result to all subsequent predictions?
- Output of Cosine Similarity is not as expected
- Getting an error while using the open ai api to summarize news atricles
- SpanRuler on Retokenized tokens links back to original token text, not the token text with a split (space) introduced
- Should I use beam search on validation phase?
- Dialogflow failing to dectect the correct intent
- How to detect if two sentences are simmilar, not in meaning, but in syllables/words?
- Is BertForSequenceClassification using the CLS vector?
- Issue with memory when using spacy_universal_sentence_encoder for similarity detection
- Why does the Cloud Natural Language Model API return so many NULLs?
- Is there any OCR or technique that can recognize/identify radio buttons printed out in the form of pdf document?
- Model, lexicon to do fine grained emotions analysis on text in r
Related Questions in SVD
- Matrix reconstruction by SVD in tensorflow
- Is polar decomposition commutative for diagonal matrices?
- Finding a polar decomposition of a matrix
- Applying Low rank approximation to learnable parameters
- SVDF layer implementation compatible with TFLite's SVDF operator
- K-rank Approximation for Image Compression Using SVD (How is Storage Size Affected?)
- Maple MTM:svd failed to converge
- I implemented an SVD, but sometimes it is not possible to restore the original matrix
- The same SVD for points with different precisions got completely different transformation matrix
- How do I keep the order of vectors after symmetric orthogonalization with Scipy?
- Python manual SVD only working for some matrices - how to stabilize it?
- truncated (partial) SVD in RcppArmadillo
- Why don't signular values of SciPy's `linalg.svd` and `linalg.lstsq` match?
- Highly wrong K matrix with DLT Camera Calibration
- SVD Decomposition for linear equation solving
Related Questions in LEMMATIZATION
- Mutating a column in a dataframe (1) based off a data in dataframe (1) that exist in another dataframe (2)
- Comparison between stemmiation and lemmatization
- LookupError in NLTK for WordNet Lemmatizer Despite Successful Download of Resources
- How to make stanza lemmatizer to return just the lemma instead of a dictionary?
- Switch spacy lemmatizer's mode for french language
- Using WordNet and the program NLTK on Python, how can I check how many lemmas each language has in WordNet?
- Adding a lemma for a new word and the concept of normalization/lemmatization in spaCy
- How to avoid lemmatizing already lemmatized sentences of a row in pandas dataframe for speedup
- How to solve an Attribute error when lemmatizing a list.lower()
- How to speed up Stanza lemmatizer by excluding reduntant words
- Library to lemmatize German compound verbs
- Sending a dataframe of Arabic text to Farasa API for lemmatization - what am I doing wrong?
- Is there a method in spacy to "normalize" feminine nouns to masculine?
- spaCY lemmatizer different results on repeated words
- re.findall does not find some dots
Related Questions in LSA
- Windows password filter dll not being loaded
- How to create a Document Term Matrix in R (using LSA)?
- Semantic similarity function in R
- Is it possible to use Latent Semantic Analysis on the fly?
- Buffer has wrong number of dimensions (expected 1, got 2). How to fit the dimensions problem?
- Google Local Service API - 500 Internal Server Error
- Finding the cosine similarity of two sentences using LSA
- Facing AttributeError: 'int' object has no attribute 'toarray' in topic modelling
- Unable to produce visualisations to calculate topic frequency for LSI model
- How do I get LSAfun to compare two rows of data in R?
- How to call LsaLookupAuthenticationPackage from Rust
- Display document to topic mapping after LSI using Gensim
- Will LSA work well on a corpus of documents of significantly different sizes?
- Search Engine: Using LSI (LSA) to enable a search in 2 languages when it is assumed that the query is only in one language
- Pooling Method in TREC competitions
Related Questions in LATENT-SEMANTIC-ANALYSIS
- Tensor Decomposition and Label-Weight Assignment in Python
- How do i retain numbers while preprocessing data using gensim in python?
- AttributeError: 'int' object has no attribute 'toarray'
- How Sklearn Latent Dirichlet Allocation really Works?
- Extracting word features from BERT model
- nltk latent semantic analysis copies the first topics over and over
- Unsupervised commands classification
- Is it possible to set the initial topic assignments for scikit-learn LDA?
- Which formula of tf-idf does the LSA model of gensim use?
- Topic Modelling: LDA , word frequency in each topic and Wordcloud
- Latent Semantic Indexation with gensim
- Latent Semantic Analysis and Stemming
- Latent text analysis (lsa package) using whole documents in R
- Semantic Similarity between Sentences in a Text
- Finding Semantic Coherence between sentences in a text
Trending Questions
- UIImageView Frame Doesn't Reflect Constraints
- Is it possible to use adb commands to click on a view by finding its ID?
- How to create a new web character symbol recognizable by html/javascript?
- Why isn't my CSS3 animation smooth in Google Chrome (but very smooth on other browsers)?
- Heap Gives Page Fault
- Connect ffmpeg to Visual Studio 2008
- Both Object- and ValueAnimator jumps when Duration is set above API LvL 24
- How to avoid default initialization of objects in std::vector?
- second argument of the command line arguments in a format other than char** argv or char* argv[]
- How to improve efficiency of algorithm which generates next lexicographic permutation?
- Navigating to the another actvity app getting crash in android
- How to read the particular message format in android and store in sqlite database?
- Resetting inventory status after order is cancelled
- Efficiently compute powers of X in SSE/AVX
- Insert into an external database using ajax and php : POST 500 (Internal Server Error)
Popular # Hahtags
Popular Questions
- How do I undo the most recent local commits in Git?
- How can I remove a specific item from an array in JavaScript?
- How do I delete a Git branch locally and remotely?
- Find all files containing a specific text (string) on Linux?
- How do I revert a Git repository to a previous commit?
- How do I create an HTML button that acts like a link?
- How do I check out a remote Git branch?
- How do I force "git pull" to overwrite local files?
- How do I list all files of a directory?
- How to check whether a string contains a substring in JavaScript?
- How do I redirect to another webpage?
- How can I iterate over rows in a Pandas DataFrame?
- How do I convert a String to an int in Java?
- Does Python have a string 'contains' substring method?
- How do I check if a string contains a specific word?
According to the founders of LSA, stemming is not necessary. Though, I think there is general disagreement in the literature about this. I have read a few papers where stemming was found to improve results for a given information retrieval task.
Generally, there is recent research that shows stemming does not help in topic modeling and may even hurt topic coherence.