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Ma Jin: Art, Achievements & Overview

Ma Jin (simplified Chinese: 马晋; traditional Chinese: 馬晉; pinyin: Mǎ Jìn; born 7 May 1988) is a badminton player from China who specialises in women's and mixed doubles. She partnered Wang Xiaoli in women's doubles and excelled in the category until 2010 when both players are split after China failed to defend their Uber Cup against South Korea in Kuala…

Language: English [EN]
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Ma Jin topic overview

The analysis highlights Art, Achievements and Overview as prominent areas in the source structure around Ma Jin.

Related topics
17
Source areas
2
Connected nodes
19
Extracted relationships
7
Related term clusters
16
Bridge connections
19

What this topic covers Research coverage

Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.

Overview · 12 topics
Achievements · 5 topics

Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.

Key facts & relationships

High-confidence facts extracted from structured source data. Use them as anchors for further research.

Born
(1988-05-07) 7 May 1988 (age 38) Nantong, Jiangsu, China
Country
China
Handedness
Right
Height
1.65 m (5 ft 5 in)
Highest ranking
1 (WD with Wang Xiaoli, 26 November 2009) 1 (XD with Zheng Bo, 21 January 2010) 1 (XD with Xu Chen, 16 August 2012)
Sport
Badminton

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Ma Jin
10Simplified Chinese characters · Traditional Chinese characters · Pinyin
7Badminton at the 2012 Summer Olympics – Mixed doubles · 2010 BWF World Championships – Mixed doubles · Badminton World Federation

Explore all related topics Closing gaps

Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.

Overview

Achievements

For the semantics nerds

You can skip this section if you’re here for content ideas and keyword inspiration.

Advanced semantic analysis

How Ma Jin connects Entity context

The extracted context around Ma Jin shows recurring relationship patterns in the source. For example, Ma Jin → (1988-05-07) 7 May 1988 (age 38) Nantong, Jiangsu, China Another extracted example is Ma Jin → China. Use these groups to spot repeated connection types before inspecting the individual relationships.

Ma Jin

Top relations

Born · 1
Ma Jin → (1988-05-07) 7 May 1988 (age 38) Nantong, Jiangsu, China
Country · 1
Ma Jin → China
Handedness · 1
Ma Jin → Right
Height · 1
Ma Jin → 1.65 m (5 ft 5 in)
Highest ranking · 1
Ma Jin → 1 (WD with Wang Xiaoli, 26 November 2009) 1 (XD with Zheng Bo, 21 January 2010) 1 (XD with Xu Chen, 16 August 2012)
Sport · 1
Ma Jin → Badminton
Weight · 1
Ma Jin → 55 kg (121 lb)

Important terminology

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

doubles mixed women's bwf ma jin world xu chen badminton china 2010 superseries zheng bo olympic chinese partner 马晋 born

Ma Jin relationships Subject–Predicate–Object triples

TTTA extracted 7 structured relationships around Ma Jin. Examples in this analysis include Ma Jin → Born → (1988-05-07) 7 May 1988 (age 38) Nantong, Jiangsu, China and Ma Jin → Country → China. The table shows each extracted connection, where it came from and its confidence.

SubjectPredicateObjectConfidenceSrc
Ma JinBorn(1988-05-07) 7 May 1988 (age 38) Nantong, Jiangsu, China1.00infobox
Ma JinCountryChina1.00infobox
Ma JinHandednessRight1.00infobox
Ma JinHeight1.65 m (5 ft 5 in)1.00infobox
Ma JinHighest ranking1 (WD with Wang Xiaoli, 26 November 2009) 1 (XD with Zheng Bo, 21 January 2010) 1 (XD with Xu Chen, 16 August 2012)1.00infobox
Ma JinSportBadminton1.00infobox
Ma JinWeight55 kg (121 lb)1.00infobox

Related concept clusters Related term clusters

The concept neighborhoods around Ma Jin bring nearby vocabulary together. In this analysis, examples include Ma, Mixed and Women's. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

  • Ma Jin
    • Ma
    • Mixed
    • Women's
    • Doubles
    • Born
    • 马晋
    • Badminton
    • Bo
    • China
    • Zheng
    • Chen
    • Xu
  • ma jin
    • Ma
    • Mixed
    • Women's
    • Doubles
    • Born
    • 马晋
    • Badminton
    • Bo
    • China
    • Zheng
    • Chen
    • Xu
  • badminton
    • Born
    • 马晋
    • China
    • Tournaments
    • World
    • Asian
    • Bwf
    • Championships
    • East
    • Games
    • Jin
    • Junior
  • china
    • Cup
    • Kuala
    • Uber
    • Wang
    • Xiaoli
    • 马晋
    • Women's
    • Doubles
    • Asian
    • Championships
    • East
    • Games
  • wang xiaoli
    • Cup
    • Kuala
    • Uber
    • Xiaoli
    • Asian
    • Championships
    • East
    • Games
    • Junior
    • Grand
    • Medal
    • Olympic
  • uber cup
    • Cup
    • Kuala
    • Uber
    • Wang
    • Xiaoli
    • Asian
    • Championships
    • East
    • Games
    • Junior
    • Grand
    • Medal
  • zheng bo
    • Zheng
    • Chen
    • Xu
    • Medal
    • Olympic
    • Silver
    • Mixed
    • World
    • Asian
    • Championships
    • East
    • Games
  • xu chen
    • Xu
    • Zheng
    • Medal
    • Olympic
    • Silver
    • Mixed
    • World
    • Jin
    • Ma
    • Asian
    • Championships
    • East

Connections between topic areas Semantic bridges

For Ma Jin, one of the stronger structural bridges in this analysis connects Ma Jin with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.

Min side: 3
Ma Jin — Overview · splits 7 ⟂ 13
Ma Jin — Achievements · splits 14 ⟂ 6

Map overview Semantic statistics

Ma Jin

Nodes20
Edges19
Triples7
Avg. degree1.9
Density0.1
Components1

Source & methodology

TTTA analyzes the structure around Ma Jin to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Art, Achievements & Overview, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — Ma Jin · EN edition · Analysis: TopicsToTalkAbout

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