MindMap Gallery Search engine mind map
A mind map helps you understand the knowledge content of search engines, including query understanding, basic word-based recall, sorting, e-commerce search, O2O search, etc.
This is a mind map about bacteria, and its main contents include: overview, morphology, types, structure, reproduction, distribution, application, and expansion. The summary is comprehensive and meticulous, suitable as review materials.
This is a mind map about plant asexual reproduction, and its main contents include: concept, spore reproduction, vegetative reproduction, tissue culture, and buds. The summary is comprehensive and meticulous, suitable as review materials.
This is a mind map about the reproductive development of animals, and its main contents include: insects, frogs, birds, sexual reproduction, and asexual reproduction. The summary is comprehensive and meticulous, suitable as review materials.
SEARCH ENGINE
SEO search engine optimization
Summary of SEO search engine optimization methods
SEO search engine optimization plan
Baidu search engine history algorithm
SEO_search engine optimization
search engine
Dasou
query understanding
Text preprocessing
query word segmentation
Based on string matching
forward maximum matching algorithm
Inverse maximum matching algorithm
Two-way maximum matching algorithm
Based on statistical word segmentation
N-Gram language model
Hidden Markov HMM
Conditional Random Field CRF
Neural language model
Based on semantic understanding
Syntactic and semantic analysis, handling ambiguity
Learn HanLP Tutorial
query rewrite
query error correction
Based on text similarity
Based on text edit distance
Based on pinyin
Collaborative filtering based on click behavior
Mining based on session
query alignment
Word similarity/external knowledge/human intervention
Generate model seq2seq
query extension
Term analysis
TF-IDF
Classification problem
Mainly weight analysis
Intent recognition
Intent classification
Named entity recognition
sequence annotation
Combining heuristic strategies/posterior actions
recall
word-based traditional recall
Boolean model
Vector space model/TF-IDF
Probabilistic Model/BM25
Vector-based semantic recall
Deep recall based on DSSM
Personalized recall based on DPSR
Based on Bert pre-training recall
...
sort
Rough row
Fine rowing
traditional method
LR
GBDT LR
FM/FFM
deep learning
Wide&Deep
strong dependency algorithm
rearrange
Business requirements
diversity requirements
More business side
Chuisou
E-commerce search
O2O search